Data Engineer Jobs with Salary ≥ 200k

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

Summary: Candidates should have 3+ years of experience in engineering management or leadership roles, particularly in data engineering or analytics. Strong communication skills and a solid understanding of cyb

Skills: data engineering, analytics, cybersecurity, python, database technologies, project management, team leadership, communication, collaboration, problem solving, continuous improvement, web harvesting, data processing, client relations, technical concepts

Summary: 8+ years of experience in data pipeline development and cloud infrastructure, with proficiency in AWS and data warehousing. Strong skills in data quality, performance optimization, and security compli

Skills: data pipeline development, cloud infrastructure, data warehousing, data quality, governance, performance optimization, security, compliance, collaboration, communication, python, sql, kafka, flink, aws, etl

Summary: Candidates should have 10+ years of experience in data engineering and 5+ years of advanced experience with Airflow and Python. Additionally, experience with Google Cloud Platform and designing produc

Skills: data engineering, python, apis, mlops, google cloud platform, bigquery, sql, data governance, data architecture, event-driven architecture, ci/cd, terraform, apache airflow, streaming pipelines, monitoring, containerization

Summary: Candidates should have over 5 years of data engineering experience, with a strong focus on AI/ML data pipelines. Proficiency in Python, SQL, and distributed data processing frameworks is essential, al

Skills: data engineering, ai, ml, python, sql, apache spark, gcp, kafka, data modeling, nosql, performance optimization, data observability, etl, data pipelines, documentation, collaboration

Summary: Candidates should have over 10 years of data engineering experience and at least 5 years of team management. A college degree in a relevant field is required, along with strong skills in data manipula

Skills: data engineering, team management, data structures, cloud technologies, mlops framework, collaboration, problem solving, data warehousing, communication skills, data manipulation, critical thinking, flexibility, technical leadership, resource optimization, analytical tools, innovative mindset

Summary: 10+ years of software development and data engineering experience with demonstrated ownership of production-grade data infrastructure. Deep expertise in scaling Spark in production and proficiency in

Skills: data engineering, pyspark, cloud platforms, data processing, analytics, ai/ml, software development, distributed computing, data modeling, python, relational databases, nosql databases, mentoring, problem solving, e-commerce integration, monitoring