Top Senior Data Engineer Jobs

Design, build, and maintain data pipelines and platforms to ingest, prepare, and organize structured and unstructured data. Develop ETL using Java/Python/SQL/Scala, work with PostgreSQL or Kafka, and leverage AWS services. Collaborate with cross-functional teams in an agile environment and support real-time/streaming applications while meeting security and clearance requirements.

As a Senior Azure Data Engineer, you will design and build data pipelines, implement data models, and lead migrations to Azure, while ensuring optimal performance and governance.

Design, build, and maintain Finance data models and scalable data pipelines on GCP. Automate workflows (Python, Airflow/Astronomer, Jenkins), ensure data governance and lineage, collaborate with stakeholders, conduct code reviews and testing, and evaluate new data sources and technologies to support financial insights.

Design and maintain data pipelines and lake platforms, optimize data processing with cloud technologies and collaborate with team members for AI initiatives.

Design, build, and maintain scalable ETL/ELT pipelines using Python/PySpark and Snowflake. Implement Snowflake objects and optimize performance, ingest structured and semi-structured data, apply dimensional modeling, enforce data quality and governance, monitor pipelines, and collaborate with architects and stakeholders to deliver cloud-based data platform solutions (Azure).

Design, implement, and optimize large-scale data processing on Databricks and Spark. Build ETL pipelines, integrate data across AWS services (Redshift, RDS), orchestrate workflows with Airflow, and ensure data warehousing and engineering best practices. Lead and mentor development teams and collaborate with cross-functional stakeholders to drive data strategy and execution.

Design, build, and maintain scalable Databricks-based ETL/ELT pipelines and analytics-ready data products on Azure and on-prem. Partner with business and engineering stakeholders to deliver end-to-end data initiatives, apply enterprise design standards, optimize production pipelines, and present technical solutions to stakeholders.

As a Senior Data Engineer, you will design and build data pipelines, manage data architecture, ensure data security, and mentor team members while collaborating across teams to create impactful data products.

The Senior Data Engineer will design and develop data pipelines, manage data architectures, ensure data security, and mentor team members, while optimizing processes for large-scale projects.

The Staff Data Engineer will lead design and implementation of analytics platforms and data products, collaborate cross-functionally, mentor engineers, and drive best practices at Upside.

Lead design and optimization of high-throughput data ingestion pipelines and Python-based microservices. Improve pipeline performance, reliability, and observability across distributed systems, define unified ingestion architectures, work with Snowflake for analytics, mentor engineers, and collaborate cross-functionally to ensure scalable, fault-tolerant data platforms.

The Lead Data Engineer designs and develops technical solutions, collaborates with Agile teams, and utilizes big data technologies, cloud computing, and full-stack development to drive digital transformation at Capital One.

Lead and mentor a data engineering team to design, develop, test, and support cloud-based big data and streaming solutions. Build full-stack data pipelines using Java/Scala/Python, RDBMS/NoSQL, Redshift/Snowflake, and cloud platforms. Collaborate with product managers, perform unit tests and code reviews, and promote engineering best practices and tech community engagement.

Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.

Design, develop, and maintain enterprise data pipelines, ETL/ELT workflows, and data management processes in Markit EDM. Integrate market, reference, and transactional data from vendors and APIs, implement data quality checks and reconciliations, support reporting and downstream integrations, troubleshoot production issues, and mentor junior engineers within an agile squad-based team.

Build and maintain enterprise data pipelines, warehouses and lakes using Java, Spark and Kafka. Lead a development team, ensure data quality, observability, security and regulatory compliance (FINRA/SEC). Implement scalable APIs on Kubernetes, authentication with OAuth2/JWT, and testing via JUnit/Mockito. Collaborate with data scientists to deploy ML models and drive data governance.

Build, test, and operationalize complex data pipelines and solutions on cloud platforms. Analyze and transform data, ensure data governance, security, and quality, troubleshoot defects, and collaborate across teams to support analytics, ML/AI, and business intelligence needs.

Design, build, and maintain cloud-based ETL pipelines and data warehouses (AWS Glue, Redshift, S3, Spark). Ensure data quality, collaborate with analysts/data scientists, document data models, monitor and troubleshoot pipelines, and adhere to federal data governance and compliance.

Design, build, and maintain scalable batch and real-time data pipelines and data lake architecture. Improve observability and SLOs, optimize ETL/ELT, develop dbt workflows, support event-driven architectures, integrate financial APIs, and collaborate with analytics and ML teams to deliver reliable, model-ready data products.

As a Senior Lead Data Engineer, you will lead teams to design technical solutions, focusing on data integration and AI capabilities to support business needs, applying your expertise in cloud computing and big data technologies.

Design, build, and maintain scalable data pipelines and cloud data infrastructure (warehouse, RBAC, validation). Collaborate with data scientists and engineers, orchestrate ML pipelines, ensure data quality/security, optimize cost and performance, lead incident response and mentor teammates.

Design, deploy, and operate large-scale Apache Kafka/Confluent streaming platforms. Own cluster sizing, configuration, security, automation, HA/DR, observability, and developer enablement. Partner with cross-functional teams to translate requirements, conduct code/design reviews, mentor junior engineers, and ensure reliable, performant production streaming systems.

Design, build, operate, and maintain production ETL/ELT pipelines, integrations, and curated datasets across enterprise systems (Salesforce, Deltek, Autodesk, Azure, Microsoft Fabric). Implement data models, orchestration, API-first services, monitoring, data quality, lineage, and governance to support BI, reporting, AI/ML, and business decision-making. Collaborate with analytics, IT/security, and business teams to ensure secure, reliable data delivery.

Design, build, operate, and maintain production ETL/ELT pipelines, integrations, and curated datasets across Salesforce, Deltek, Autodesk, Azure, and Microsoft Fabric. Implement data models, orchestration, API-first services, monitoring, data quality, governance, and support AI/ML and BI initiatives while partnering with stakeholders to ensure secure, reliable data delivery.

Design, build, and own Sardine's internal data platform and billing infrastructure. Implement and maintain ETL/ELT pipelines, warehouse partitioning, access controls, and data governance. Partner with stakeholders to define KPIs, produce dashboards, and ensure data quality for executive, GTM, product, and finance teams.