Data Engineer Jobs with Salary ≥ 200k

Summary: A strong background in both data and software engineering with at least 2 years of relevant experience is required. Proficiency in programming languages and excellent debugging skills are essential.

Skills: data engineering, software engineering, python, sql, debugging, technical communication, retl tools, bigquery sql, airflow, dbt, django orm, product analytics, medallion architecture, technical writing, mentoring

Summary: Design and maintain data pipelines and infrastructure for BI and AI decisions; own data models for RCM, intake, and clinical ops; requires SQL, Databricks/Redshift, and Airflow/dbt.

Skills: sql, postgresql, mysql

Summary: The role requires 7+ years of experience in data engineering, particularly with high-volume consumer data in advertising. Candidates should have expert-level coding abilities in SQL and Python, along with experience in building high-throughput data pipelines.

Skills: data engineering, sql, python, etl processes, data models, data quality, monitoring systems, anomaly detection, collaboration, technical leadership, data visualization, dashboarding, advertising technology, machine learning, data infrastructure, problem solving

Summary: Candidates must have a Bachelor’s Degree and at least 7 years of experience in data engineering, with 5 years in data architecture. Preferred qualifications include a Master’s Degree and extensive experience with various programming languages and data tools.

Skills: data engineering, data architecture, python, java, go, sql, kafka, airflow, spark, aws glue, kinesis, databricks, snowflake, machine learning, mentoring, collaboration

Summary: Candidates must have 15+ years of experience in a data-centric role and be expert in Python and SQL. Hands-on experience with Snowflake and advanced knowledge of Tableau are also required.

Skills: python, sql, snowflake, tableau, data pipelines, data transformation, analytics workflows, product kpis, collaboration, data quality, business metrics, user behavior, feature usage, data models, stakeholder engagement, cloud platforms

Summary: A minimum of 6 years of experience in software or data engineering is required, along with proficiency in programming languages such as Python, SQL, and Java. Candidates should have a strong understanding of data warehousing concepts and experience with ETL processes and data streaming technologies.

Skills: python, sql, java, data warehousing, etl processes, database management, data streaming, apache kafka, aws kinesis, apache flink, apache spark, devsecops, github, agile, cloud platforms, geospatial data

Summary: Candidates must have a Bachelor’s Degree and at least 6 years of application development experience. Preferred qualifications include a Master's Degree and extensive experience with big data technologies and cloud computing.

Skills: data engineering, machine learning, distributed microservices, full stack development, java, scala, python, rdbms, nosql, cloud computing, agile engineering, data warehousing, unix/linux, streaming applications, data governance, infrastructure management

Summary: Candidates should have 8+ years of experience in data engineering, including 3+ years in a leadership role. Proven expertise in relevant technologies and a strong background in collaborating with analytics and BI teams is essential.

Skills: data engineering, leadership, airflow, dbt, python, kafka streaming, snowflake, api-based data ingestion, real-time streaming, data pipeline orchestration, data integration, analytics, ai assistance bot integration, devops, ci/cd practices, data governance

Summary: The role requires 8+ years of experience in designing and scaling data systems, with proven technical leadership in complex data ecosystems. Candidates should have deep experience with modern data stacks and strong collaboration skills.

Skills: data engineering, data architecture, sql, python, data quality, data integration, cloud-native warehouses, orchestration tools, transformation frameworks, collaboration, mentorship, data systems, real-time data products, apache kafka, analytics, machine learning

Summary: Candidates should have 3+ years of experience in data engineering or backend engineering with a strong data focus. A deep understanding of modern data architecture and strong programming skills in Go or Python are essential.

Skills: data engineering, backend engineering, data architecture, etl, elt, go, python, sql, aws, kubernetes, data security, data reliability, data visualization, data governance, blockchain, analytics

Summary: Candidates must have a mastery of 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 required, along with 5-7 years of relevant work experience.

Skills: software engineering, data engineering, leadership, mentoring, collaboration, java, python, sql, automation, cloud technologies, vendor management, agile methodologies, problem solving, system monitoring, technical escalation, data systems

Summary: Candidates should have over 10 years of experience in senior engineering roles, with at least 5 years as a technical lead. Experience with compliance, particularly in FedRAMP or DoD environments, is also required.

Skills: technical leadership, cross-functional collaboration, mentorship, strategic impact, compliance experience