Top Senior Data Engineer Jobs

The Senior Data Engineer will design and build data pipelines, manage data architecture, ensure privacy compliance, mentor team members, and collaborate with cross-functional teams.

Lead design, develop, test, and support cloud-based data platforms and scalable data pipelines. Mentor engineers, collaborate with product managers, and deliver high-performance data lakehouse/warehousing and event-driven solutions using big data and cloud technologies.

Design, build, and scale high-volume data pipelines and architectures. Lead end-to-end data projects, improve feature engineering and models, ensure data quality and security, perform code reviews, and collaborate with data scientists and business stakeholders to deliver actionable insights.

Design, build, and maintain scalable AWS data pipelines and data lakes. Migrate legacy data to AWS, implement ETL/ELT, optimize storage and query performance, and enforce data quality, governance, and monitoring while collaborating with DBAs, data scientists, and stakeholders.

Senior Addepar data engineer/analyst responsible for supporting and scaling Addepar integrations, building and maintaining data pipelines (Addepar↔Snowflake/Canoe/other platforms), diagnosing and resolving data quality issues, developing SQL-based reconciliations and automation, partnering with business and technology stakeholders, and supporting production operations, governance, testing, and documentation for wealth and asset management data.

Design, build, and own the pursuit intelligence platform integrating GovWin IQ, SAM.gov, Salesforce, and D&B. Lead API integrations, ETL/ELT pipelines, account scoring/tiering engines, and data architecture. Provide technical leadership through code reviews, coaching, documentation, and standards to support business intelligence and Go/No-Go decisioning for Pursuit & Capture.

Design, build, and maintain cloud-based ETL pipelines and data models for finance. Implement data security (RLS), semantic layers for Power BI, monitor data integrity, support analytics/AI initiatives, and collaborate with Finance, Accounting, and IT to deliver high-quality BI solutions.

Design and deliver Databricks lakehouse solutions: build ETL/ELT pipelines with PySpark and SQL, implement governance and Unity Catalog, integrate data platforms with applications via APIs/events, apply cloud architecture best practices, automate CI/CD for Databricks workloads, and consult with clients on requirements and solution design.

As a Data Engineer, you will design and maintain data pipelines, support DoD systems, and ensure data quality and compliance.

Design, build, and maintain scalable batch and near-real-time data ingestion, transformation, and curation pipelines using Databricks and AWS. Support full pipeline lifecycle (intake, profiling, development, testing, release), implement data quality and observability, enforce metadata/lineage/governance, integrate with enterprise services, and prepare curated datasets for SQL and BI consumption.

Build and maintain production data pipelines and model implementations for Property and General Liability pricing. Collaborate with Actuarial and Data Science to translate requirements into scalable, cloud-native solutions, embed MLOps practices, establish data quality controls, provide technical leadership, and support modernization and monitoring for pricing models.

Build and maintain scalable, high-availability data systems and ELT pipelines combining sensor, financial, and commodity data. Design enterprise data solutions, optimize storage and retrieval, ensure data quality, and partner with stakeholders to enable analytics across the business.

Design, build, and maintain scalable data pipelines and transformations using Snowflake, Airflow, and CI/CD. Ensure data quality, de-identification, monitoring, and optimization. Collaborate with architects, analysts, and stewards to meet business requirements and implement robust, production-ready data solutions.

As a Senior Data Engineer, you will automate processes, optimize data handling, build data products, and govern data while mentoring junior engineers.

Design, build, and support secure, scalable cloud data solutions and ETL pipelines (PySpark) for regulatory reporting and analytics. Lead technical solution design, implement CI/CD with Azure DevOps, enforce data governance, quality, and compliance, produce documentation, mentor teams, and collaborate with stakeholders to align data architecture with business goals.

Design, build, and operate enterprise data pipelines and Lakehouse data products on Azure. Lead migrations, implement medallion architectures, optimize Spark and distributed SQL workloads, enforce CI/CD and observability, and support production incident response while partnering with architects, data scientists, and stakeholders.

Design, build, and operate scalable Databricks-based data ingestion and transformation pipelines on AWS. Ensure governed, observable, production-grade lakehouse solutions with metadata, lineage, data quality, security controls, and CI/CD deployment to support analytics and regulatory compliance.

Design, build, and optimize data pipelines for massive datasets. Collaborate with stakeholders, implement CI/CD processes, and ensure data architecture scalability.

Lead design and hands-on delivery of a next-generation data platform and pipelines (batch, ELT, near-real-time) powering BI, experimentation, and ML. Own platform architecture, data modeling, governance, observability, and mentor engineers while modernizing legacy systems and driving AI-first data engineering practices across cross-functional teams.

Lead architecture and delivery of a cloud-native, petabyte-scale data platform: define technical roadmap, mentor engineers, build ETL/ELT pipelines, enable real-time streaming, implement Iceberg table format, optimize Snowflake/Redshift/Athena compute, and integrate observability with Splunk.

Lead end-to-end data engineering on GCP: design scalable data platforms and architectures (lake/lakehouse/warehouse), build and optimize BigQuery/Spark pipelines, ensure data quality/security, enable ML workflows with Data Science, mentor engineers, and own delivery and performance.

Design, build, and optimize scalable AWS-based data pipelines, data lakes, and warehouses. Migrate legacy systems, enforce data quality/security/governance, implement ETL/ELT and big-data solutions, adopt CI/CD and IaC, collaborate with stakeholders, and provide technical leadership and troubleshooting.

Design, build, modernize, and maintain operational and analytical data capabilities for Wealthscape Reporting, Analytics and Insights. Perform solution design, data analysis, ETL development, and production rollouts using Snowflake, AWS, cloud databases, and CI/CD pipelines. Collaborate across teams in a fast-paced financial services environment.

Design, build, and maintain scalable data pipelines on AWS using EMR, Spark, and PySpark. Optimize EMR clusters and Spark jobs, implement ETL/ELT processes, ensure data quality, automate ingestion, and collaborate with data scientists and analysts. Document infrastructure, participate in code reviews, and monitor performance and costs.

Design, build, and maintain ETL/ELT data pipelines and orchestration using Airflow, Python, and PySpark. Develop custom connectors, implement DataOps and CI/CD for data workflows, monitor and troubleshoot pipelines, validate data quality, and document processes while collaborating with cross-functional teams and supporting large-scale distributed data systems.