Data Engineer Jobs with Salary ≥ 80k

Summary: Candidates should have experience in building production data pipelines and operating data streaming solutions on Kubernetes. Familiarity with cybersecurity principles and excellent problem-solving sk

Skills: data engineering, etl, elt, aws, kubernetes, kafka, redpanda, terraform, cybersecurity, api security, container security, problem-solving, communication, machine learning, generative ai, infrastructure-as-code

Summary: Design and manage data pipelines using Python, Airflow, and SQL to support pricing models and analytics.

Skills: python, airflow, sql

Summary: Candidates should have 5-8+ years of experience in data engineering with strong hands-on experience in Snowflake, Airflow, and AWS. Proficiency in Python and SQL is required, along with the ability to

Skills: data engineering, snowflake, airflow, aws, python, sql, etl, elt, data governance, ai, ci/cd, github, data quality, data lineage, data observability, mentoring

Summary: A minimum of 8 years of industry experience in data infrastructure/data engineering is required. Familiarity with AWS services and strong fundamentals in data structures and algorithms are also essent

Skills: data infrastructure, data engineering, python, sql, dbt, snowflake, infrastructure as code, cdk, terraform, aws, kafka, hadoop, spark, nosql, ci/cd, machine learning, business intelligence

Summary: You should have experience building data pipelines and working with ETL systems, as well as proficiency in SQL and programming in Python and Java. Familiarity with big data technologies and healthcare

Skills: data pipelines, etl systems, sql, data warehouse, python, java, big data technologies, kafka, spark, healthcare data formats, hl7, fhir

Summary: Candidates should have a minimum of 5 years of experience in software engineering or data engineering, with strong programming skills in Python, SQL, and Java. Familiarity with modern data lakehouse t

Skills: data engineering, etl processes, data pipelines, cloud technologies, python, sql, java, data streaming, apache kafka, aws kinesis, apache flink, apache spark, devsecops, agile, machine learning, data warehousing

Summary: Candidates should have 7+ years in data engineering, including 2+ years in a lead role, with strong expertise in Python and SQL. Experience in designing and scaling data platforms in a high-growth env

Skills: python, sql, data engineering, data modelling, data architecture, orchestration frameworks, mentoring, data pipelines, analytics, aws, snowflake, apache iceberg, infrastructure-as-code, observability, automation, version control

Summary: Candidates must have a bachelor's degree in a quantitative field or equivalent experience in Information Technology. Hands-on experience with SQL, Hadoop, and programming in Scala, Java, or Python is

Skills: data engineering, hadoop, nosql, kafka, spark, ab initio, sql, shell scripting, data quality, data governance, agile methodology, data analysis, cloud services, etl, data warehousing, collibra

Summary: The ideal candidate will have 5+ years of experience building large-scale, real-time distributed systems and proficiency in Python and SQL. Familiarity with event-driven architectures and cloud platfo

Skills: data engineering, python, sql, java, scala, nosql, data pipelines, event-driven architectures, messaging frameworks, cloud platforms, erp solutions, hcm solutions, ci/cd, testing, secure coding, collaboration

Summary: The ideal candidate should have a bachelor's degree in a related field and 4-6 years of professional experience in data engineering. Proficiency in SQL and experience with high-performance data pipeli

Skills: data engineering, sql, snowflake, informatica, data pipelines, data management, devops, ci/cd, automation, data quality, real-time processing, mentoring, problem-solving, communication, organizational skills

Summary: Candidates must have 5+ years of data engineering experience and familiarity with multiple cloud platforms. Strong analytic skills and experience with big data tools are also required.

Skills: data engineering, cloud platforms, sql, data modeling, machine learning, data analysis, big data, hadoop, spark, kafka, data quality, data governance, data pipelines, documentation, data security, business intelligence

Summary: Candidates should have at least 3 years of experience in engineering data systems and strong skills in relational database schema design. Experience with cloud infrastructure DevOps and excellent comm

Skills: data engineering, spark, beam, flink, relational database, devops, communication, ownership, craftsmanship

Summary: 3+ years of experience with large-scale data and query optimization techniques is required. Proficiency in SQL and experience with AWS cloud services are essential.

Skills: data engineering, sql, aws, etl, data visualization, problem solving, scripting, cloud services, nosql, rdbms, data structures, algorithms, distributed systems, stream-processing, communication, teamwork

Summary: Candidates must have significant experience in software engineering, particularly with Golang and Python, and a strong understanding of data architecture. A relevant degree and extensive experience in

Skills: golang, python, api design, google kubernetes engine, google cloud platform, microservices, event-driven architecture, ci/cd, infrastructure as code, data architecture, observability, apache kafka, sql, git, machine learning, generative ai

Summary: Candidates should have over 5 years of experience in building data infrastructure and proven skills in ETL/ELT workflows. Expertise in SQL and familiarity with cloud-based architectures, particularly

Skills: data engineering, etl, data pipelines, sql, python, aws, data modeling, cloud architecture, ci/cd, monitoring, data integrity, data quality, automation, infrastructure-as-code, analytics, business intelligence

Summary: Candidates should have a Bachelor's Degree or equivalent experience, with a track record of shipping and maintaining software products in Go. Extensive experience in system design for large-scale appl

Skills: go, data engineering, software craftsmanship, algorithms, data structures, system design, architecture, apache kafka, unit testing, test driven development, docker, kubernetes, cloud infrastructure, data modeling, bioinformatics, grpc

Summary: Candidates must have significant knowledge of the crypto industry and at least 4 years of hands-on experience with data modeling, schema design, and data warehousing. Proficiency in programming langua

Skills: data architecture, data engineering, data modeling, schema design, data operations, data warehousing, typescript, go, python, sql, postgresql, etl solutions, blockchain, devops, solana, microservices, automation

Summary: Candidates should have a bachelor's degree in Computer Science or a related field and at least 5 years of experience in building and maintaining data-intensive applications. Proficiency in modern data

Skills: data engineering, data pipelines, data modeling, python, java, scala, sql, spark, airflow, cloud platforms, databricks, data visualization, collaboration, automation, mentoring, troubleshooting

Summary: Candidates should have at least 10 years of professional software engineering experience, with 5 years leading other software engineers. Expertise in data architecture, ELT development, and proficienc

Skills: data architecture, business intelligence, elt development, data transformation, data modeling, report design, python, typescript, sql, infrastructure as code, aws, etl tooling, kinesis data streaming, tableau, hipaa, soc, hitrust

Summary: Candidates should have at least 10 years of professional software engineering experience, with 5 years leading other engineers and expertise in data architecture and business intelligence systems. Pro

Skills: data architecture, business intelligence, elt development, data transformation, data modeling, report design, python, typescript, sql, infrastructure as code, aws, etl tooling, kinesis, tableau, hipaa, golang

Summary: Candidates should have 5+ years of experience in data engineering and strong SQL skills. They must demonstrate the ability to work autonomously and have hands-on experience managing cloud data warehou

Skills: data engineering, sql, data pipelines, data modeling, cloud data warehouses, postgres, airbyte, dbt, tableau, data governance, analytics, business intelligence, etl, data quality, cross-functional collaboration, mentorship

Summary: Candidates should have a Bachelor's or Master's degree in a related technical discipline and a minimum of 3 years of software development experience on secure, cloud-based platforms. Strong programmin

Skills: data engineering, etl pipelines, data integration, python, pyspark, spark, hive, hadoop, cloud-based solutions, problem-solving, mentoring, collaboration, documentation, continuous improvement, data analysis, testing

Summary: Candidates should have a Bachelor's or Master's degree in a related technical discipline and at least 7 years of professional experience in software development, preferably in cloud-based environments

Skills: data engineering, cloud-based solutions, python, java, apache spark, hadoop, data governance, distributed systems, project management, technical leadership, problem solving, mentoring, collaboration, software development, data architecture, analytics technologies

Summary: 15+ years of experience in data engineering and analytics platforms, including 7+ years in senior leadership roles. Expertise in cloud data warehouses and experience supporting AI/ML teams through adv

Skills: data engineering, enterprise integrations, analytics platforms, technical leadership, architecture design, pipeline development, sales systems, marketing systems, finance systems, ai/ml support, cloud data warehouses, orchestration tools, integration platforms, real-time pipelines, sql, python

Summary: Candidates must have a bachelor's degree in a related field and at least 7 years of experience in data engineering and ETL development. Supervisory experience and familiarity with cloud environments a

Skills: data engineering, etl development, data warehousing, data visualization, sql, java, xml, cloud computing, aws, azure, talend, ssis, snowflake, business intelligence, data analytics, metadata management, database security

Summary: 15+ years of experience in data engineering and analytics platforms, with 7+ years in senior leadership roles. Proven ability to manage global teams and deliver scalable solutions in high-growth envir

Skills: data engineering, enterprise integrations, analytics platforms, sales tech stacks, marketing tech stacks, finance systems, ai/ml support, data infrastructure, cloud data warehouses, orchestration tools, integration platforms, data ingestion, sql, python, cloud platforms, data modeling

Summary: Candidates should have 4+ years of professional experience as a data engineer, with expertise in SQL and dbt. Familiarity with workflow orchestration tools like Airflow and strong problem-solving skil

Skills: sql, dbt, workflow orchestration tools, airflow, data quality, data pipelines, analytics, collaboration, problem-solving, ai, automation, communication, etl, data models, data documentation, metrics design

Summary: Candidates should have a bachelor's degree in a quantitative or technical field and 4-6 years of experience in data engineering or related fields. Strong knowledge of data pipeline development, ETL/EL

Skills: data engineering, data pipelines, etl, sql, informatica, snowflake, data modeling, real-time processing, batch processing, data quality, data governance, cloud-based platforms, devsecops, problem-solving, analytical skills, communication skills

Summary: Candidates should have 2-4 years of professional experience in Data Engineering and Data Warehousing, with strong skills in Python and SQL. Experience with ETL/ELT processes, cloud infrastructure, and

Skills: data engineering, data warehousing, python, parquet, spark, azure databricks, sql, etl, elt, data modelling, bi visualization, ci/cd, cloud infrastructure, master data management, communication, collaboration

Summary: Active DHS CBP Public Trust Clearance or higher is required. Candidates should have 2-4 years of industry experience in Data Engineering and coding commercial software.

Skills: python, aws, hadoop, spark, kafka, postgres, cassandra, azkaban, luigi, airflow, ec2, emr, rds, redshift, storm, elasticsearch

Summary: Candidates should have a Bachelor's Degree in a relevant field and 5 to 10 years of experience in Software Engineering or Data Engineering. Knowledge of Databricks, Spark, and experience with AWS serv

Skills: data engineering, big data, data analysis, cloud computing, aws, databricks, python, spark, data pipelines, data wrangling, machine learning, software development, data modeling, data integration, agile, linux

Summary: Candidates must have a Bachelor's Degree in a relevant field and 5 to 10 years of experience in Software Engineering or Data Engineering. Knowledge of Databricks, Spark, and experience with AWS servic

Skills: data engineering, big data, aws, databricks, python, spark, data analysis, data pipelines, data wrangling, machine learning, software engineering, data modeling, agile, linux, data visualization, kafka

Summary: Candidates must have a BS degree in Computer Science or related field with 3+ years of experience, or a Master's degree with 2+ years of experience. Proficiency in Databricks, Python, Spark, and data

Skills: databricks, azure, data engineering, etl, ai technologies, python, spark, r, data governance, agile, ci/cd, infrastructure-as-code, data quality, data management, cost optimization, data analytics

Summary: Candidates must have a BS/BA degree in a related field and at least 5 years of experience in writing production-level code, particularly in Python and SQL. Knowledge of sports betting and familiarity

Skills: python, sql, airflow, kubernetes, etl pipelines, rest apis, git, continuous integration, deployment, shell scripting, cloud computing, aws, web scraping, data cleaning, data science, machine learning

Summary: Candidates should have a bachelor's degree in a related field or equivalent experience, along with 3+ years of experience with Microsoft data and business intelligence solutions. Strong communication

Skills: azure data platform, power bi, data engineering, data analytics, data pipelines, ai-driven solutions, client relationship skills, problem solving, microsoft azure, synapse, data factory, databricks, data lake, data warehouse, itil, documentation

Summary: The role requires 5+ years of experience with Microsoft’s Azure data stack and experience in a dynamic startup environment. Candidates should be comfortable translating ambiguous data needs into actio

Skills: azure data factory, azure synapse analytics, microsoft power bi, etl pipelines, data warehousing, python, data modeling, data aggregation, data analysis, agile practices, collaboration, troubleshooting, documentation, software development, data pipelines, stakeholder interaction

Summary: Candidates should have 3+ years of experience building scalable data pipelines in a cloud-native environment and 2+ years of experience using dbt, Flink, or Spark for data transformations. Advanced pr

Skills: data pipelines, cloud-native environment, aws, gcp, azure, dbt, flink, spark, python, sql, apache kafka, apache flink, gcp datastream, aws kinesis, ci/cd pipelines, infrastructure-as-code, data quality

Summary: Candidates should have over 3 years of experience with SQL, Python, and dbt for data processing and modeling. Familiarity with data orchestration tools and strong communication skills are also require

Skills: sql, python, dbt, airbyte, dagster, data quality, agile, communication, bi tools, reverse etl, data governance, aws, machine learning, infrastructure-as-code, containerization

Summary: Candidates must have mastery in an object-oriented programming language, preferably Java, and a modern scripting language, preferably Python. A bachelor's degree or equivalent in a related field is re

Skills: java, python, ruby on rails, spring mvc, node.js, sql, git, html, css, javascript, angularjs, reactjs, linux, ci/cd, microservices, restful web services

Summary: A Bachelor's degree in Data Science or a closely related discipline is required, along with 5 years of experience. Candidates must have 2-4 years of experience with MS SQL Server and SSIS, as well as

Skills: big data, data engineering, data modeling, data tools, structured query language (sql), microsoft data stack, python, etl, cloud services, data warehousing, agile, hadoop, spark, kafka, relational databases, nosql databases

Summary: Candidates should have a bachelor's degree in a related field and at least 2 years of experience in data engineering. Strong skills in Python and SQL, along with experience in data warehousing technol

Skills: python, sql, data warehousing, etl, elt, gcp, snowflake, dbt, data quality, data governance, ci/cd, collaboration, problem-solving, analytical skills, software engineering, infrastructure-as-code

Summary: Candidates should have 7+ years of hands-on data engineering experience and a graduate degree in a related field. Strong skills in SQL, data modeling, and proficiency in programming languages such as

Skills: data engineering, data pipelines, etl processes, data integration, sql, data modeling, python, golang, java, scala, apache spark, kafka, data governance, orchestration tools, cloud-based solutions, project management, communication

Summary: Bachelor’s degree in a related technical field and 5+ years of experience in data engineering or full-stack development are required. Strong SQL skills and proficiency in Python, Java, or Scala are es

Skills: data engineering, cloud architecture, genai, llm workflows, etl, elt, sql, python, java, scala, apache airflow, aws glue, aws, azure, gcp, data validation, leadership

Summary: The ideal candidate should have hands-on experience with data governance and proficiency in Python and SQL. A strong sense of accountability for customer data privacy and the ability to translate gove

Skills: data governance, metadata frameworks, python, sql, relational schema design, access control, aws, data infrastructure, data quality, apis, automation, compliance, privacy, data catalog, data privacy, ai

Summary: Candidates must have a bachelor's degree with at least 2 years of experience in data engineering and database management. Proficiency in SQL and experience with data pipelines and ETL tools are requir

Skills: data engineering, sql, database management, data pipelines, etl, cloud solutions, data warehousing, data quality, data security, agile methodologies, collaboration, problem-solving, automation, data architecture, infrastructure as code, scripting

Summary: Candidates should have 3+ years of experience for the Data Engineer role or 8+ years for the Senior Data Engineer role in cloud-based data engineering. Proficiency in SQL and Python, along with knowle

Skills: data engineering, cloud-based solutions, bigquery, etl processes, sql, python, data modeling, data warehousing, agile frameworks, problem-solving, data quality, collaboration, technical guidance, data governance, workflow automation, scalability

Summary: Candidates should possess 4+ years of experience in cloud-based data engineering for Data Engineer and 7+ years for Senior Data Engineer, with strong skills in SQL, Python, and optionally Scala. A Bac

Skills: data engineering, ai, ml, cloud-based solutions, sql, python, scala, etl processes, data warehousing, big data architecture, agile frameworks, data modeling, infrastructure-as-code, data integrity, problem-solving, communication

Summary: Candidates should have 3+ years of experience with Google BigQuery for Data Engineer and 5+ additional years for Senior Data Engineer. Proficiency in SQL, Python, and experience with cloud-native serv

Skills: data engineering, gcp, bigquery, etl, sql, python, terraform, kubernetes, looker, data modeling, cloud services, ci/cd, version control, data lake, automation, problem solving

Summary: Candidates should have a bachelor's degree and over 5 years of experience in data analytics or engineering, preferably in a SaaS environment. Proficiency in SQL and experience with Databricks and Pyth

Skills: data engineering, sql, python, databricks, snowflake, data modeling, documentation, version control, excel, google sheets, data visualization, looker, strategic thinking, project management, automation, agile

Summary: 3+ years of professional experience as a Data Engineer in cloud environments is required. Strong experience with AWS services and big data architectures is essential.

Skills: data engineering, aws, python, apache spark, kinesis, airflow, terraform, data governance, ci/cd, data pipelines, big data, real-time data streaming, containerization, infrastructure as code, monitoring, collaboration

Summary: Candidates should have 3-6 years of professional software engineering experience with a strong portfolio in full stack development. Proficiency in Python and cloud experience, particularly with AWS, a

Skills: python, full stack development, aws, restful apis, sql server, snowflake, mongodb, debugging, issue resolution, troubleshooting, ux design tools, containerization, infrastructure as code, cicd tools, financial systems, credit modeling

Summary: 5+ years of professional experience in data engineering, ideally in the insurance or financial services sector. Proficiency in Python, SQL, and Spark, with hands-on experience in Databricks and AWS da

Skills: python, sql, spark, databricks, unity catalog, delta lake, dlt pipelines, data governance, data quality, aws, github, ci/cd, mentoring, problem-solving, cloud services, data architecture

Summary: Candidates should have over 5 years of experience in building and maintaining ETL pipelines and a strong background in SQL and Python. A bachelor's degree in a relevant field is required.

Skills: data engineering, etl pipelines, sql development, python development, data transformation, data access patterns, data modelling, data serialization, json-based storage, communication skills, monitoring strategies, incident response, data optimization, machine learning, data frameworks, data tools

Summary: Candidates must possess a BS degree in Computer Science or related field with 3+ years of experience, or a Master's degree with 2+ years of experience. Proficiency in Python, Spark, and R is essential

Skills: databricks, data engineering, azure, etl, ai technologies, python, spark, r, data governance, agile, ci/cd, infrastructure-as-code, data quality, data management, cost optimization, data analytics

Summary: Candidates should have 1 to 4 years of experience in data engineering or analytics engineering, with strong SQL and Python skills. Familiarity with cloud data warehouses and tools like dbt is essentia

Skills: data engineering, sql, python, cloud data warehouses, dbt, airflow, data modeling, healthcare data, git, looker, data pipelines, data integrity, data transformation, collaboration, problem solving, communication

Summary: You should have a track record of delivering scalable service components and experience with Python. Familiarity with public cloud concepts, especially GCP, and a proactive mindset for continuous impr

Skills: python, api development, data pipelines, microservices, data dashboards, data models, etl pipelines, public cloud, gcp, bigquery, bigtable, pub/sub, infrastructure as code, containerization, data governance, testing practices

Summary: Strong SQL skills on multiple platforms and some scripting language experience, preferably Python, are required. Candidates should have strong data engineering experience and familiarity with analytic

Skills: sql, mssql, mysql, postgres, spark, python, data engineering, power bi, tableau, qlik, power platform, data warehousing, azure, databricks, snowflake

Summary: B.S degree in Computer Science or a related field with 5+ years of experience in Software Engineering or Data Engineering roles. Experience with Python, Spark, Java, Scala, Big Data Technologies, SQL,

Skills: python, spark, java, scala, big data technologies, sql, etl tools, dbt, streaming tools, kafka, kinesis

Summary: Candidates should have a B.S. degree in Computer Science or a related field and at least 5 years of experience in Software Engineering or Data Engineering roles. Proficiency in programming languages s

Skills: python, spark, java, scala, big data technologies, sql, etl tools, dbt, streaming tools, kafka, kinesis

Summary: Candidates should have a Bachelor's degree or equivalent experience with 5+ years in data engineering or related roles. Strong experience with AWS and ETL tools, proficiency in Python/PySpark, and kno

Skills: data engineering, etl, aws, python, pyspark, cloud technologies, data modeling, data processing, snowflake, ci/cd, agile, database security, problem solving, analytical skills, communication skills

Summary: Candidates should have 5+ years of experience in data engineering and strong proficiency in Python and SQL. Familiarity with modern data platforms and hands-on experience with tools like Spark and Air

Skills: python, sql, etl, data engineering, data quality, data governance, data security, data integration, spark, pyspark, airflow, docker, git, databricks, microsoft azure, delta lake

Summary: Candidates should have 7+ years of experience in data engineering or a similar role, with expertise in SQL Server, Tableau, R, and Python. A bachelor's degree or equivalent experience is required, and

Skills: data engineering, sql server, postgresql, tableau, r, python, dataiku, predictive analysis, data administration, data warehousing, star schemas, visualization techniques, problem-solving, analytical skills, attention to detail, communication skills, collaboration skills

Summary: Candidates should have a Bachelor’s or Master’s degree in a related field and at least 10 years of engineering experience, including 3 years of direct people management. Preferred qualifications inclu

Skills: data engineering, data platforms, ingestion frameworks, transformation tools, serving layers, leadership, team building, operational processes, metrics, analytics, ai/ml, security, governance, compliance, problem-solving, cost transparency

Summary: Candidates should have a degree in Computer Science or a related field, along with 5+ years of experience in data engineering or software development. Advanced knowledge of software engineering concep

Skills: data engineering, software development, cloud computing, azure, sql, python, devsecops, collaboration, client-centric solutions, continuous improvement, security standards, scalability, performance optimization, data analytics, solution design, technical leadership

Summary: You should have 4+ years of experience in Data Engineering with advanced SQL skills and expertise in cloud-based data platforms. A strong understanding of data architecture and the ability to lead pro

Skills: data engineering, sql, cloud-based data platforms, data architecture, dimensional modeling, agile software development, mentoring, version control, data quality, data pipelines, data models, system monitoring, performance optimization, business logic, data processing, collaboration

Summary: The role requires 12+ years of experience in data pipeline automation and expertise in scripting languages like Python and SQL. A Bachelor's Degree in Computer Science or a related IT discipline is re

Skills: data pipeline automation, cloud api, automation frameworks, data modeling, etl processes, sql, python, dbt, apache airflow, data integration, data quality, data management, ci/cd processes, github, cloud databases, scripting languages

Summary: Candidates should have 5+ years of professional data engineering experience and a BS or MS in Computer Science, Data Science, or a related field. Expertise in AWS, Databricks, and modern data engineer

Skills: data engineering, cloud-native solutions, aws, databricks, python, sql, etl, data warehousing, apache spark, agile, data modeling, delta lake, performance tuning, data quality, collaboration, technical leadership

Summary: Candidates should have 15+ years of experience in building and scaling data teams, with a strong focus on data strategy and architecture. A graduate degree in Computer Science or a similar field is re

Skills: data strategy, infrastructure planning, architecture, data products, microservices, restful apis, devops, ci/cd, data observability, monitoring, lineage, bi tools, tableau, amplitude, redash, data science, machine learning

Summary: Candidates should have a bachelor's degree in a related field and 2-4 years of experience in data engineering. Proficiency in SQL, Python, and familiarity with Azure DevOps and cloud platforms is requ

Skills: data engineering, sql, python, data modeling, cloud platforms, azure, problem-solving, analytical skills, communication, collaboration, big data technologies, data warehousing, data security, compliance requirements

Summary: Candidates should have a bachelor's degree in a related field and at least 7 years of experience in software or data engineering. Proficiency in Java, Python, and experience with SQL/NoSQL databases a

Skills: java, python, microservices, apis, sql, nosql, data pipelines, data integration, data validation, monitoring strategies, troubleshooting, technical documentation, collaboration, healthcare informatics, billing systems, interoperability standards

Summary: Candidates should have 8+ years of experience in data engineering with a strong focus on scalability and hands-on engineering expertise. Familiarity with GCP, BigQuery, and experience in the healthcar

Skills: data engineering, data platform operations, data storage systems, cloud computing, data modeling, batch data processing, problem-solving, collaboration, communication, gcp, bigquery, dbt, dagster, healthcare domain, medical data

Summary: Bachelor’s degree in a relevant field and 5+ years of experience in data engineering or related roles are required. Proven experience with large-scale data technologies and strong problem-solving skil

Skills: data engineering, etl, python, go, java, rust, airflow, spark, kafka, sql, data architecture, collaboration, problem solving, database management, graphql, devops