Top Senior Data Engineer Jobs

Lead design and implementation of scalable real-time and batch data pipelines for programmatic advertising. Ingest, normalize, transform, and model bid stream, impression, and revenue data; maintain data warehouses and lakes; implement data quality and privacy compliance; support BI teams and optimize yield through analytics and feature engineering.

Design, build, and optimize enterprise-scale data pipelines and data models in Databricks to support analytics, AI, and operational systems. Lead MDM initiatives, implement data governance, lineage, and quality frameworks, and collaborate with engineering and business teams to ensure scalable, reliable, and cost-efficient data platforms.

Design, build, and deploy an ETL-based transactional data system to read and manage information state and transmit data via web services. Implement solution from provided design, perform unit testing, deploy to development/test, and collaborate with QA and DPS to resolve defects.

The Senior Data Engineer will design and build data pipelines and infrastructure to support data science and business intelligence solutions, utilizing AWS services and streaming technologies.

Lead the technical direction for data platforms, develop high-throughput data processing systems, mentor engineers, and ensure production reliability.

Design, ingest, validate, and manage complex financial and annuity data from external partners. Build and maintain ETL pipelines, SQL queries, and data quality controls; investigate data anomalies; collaborate with Accounting, Actuarial, and Technology; support reporting and process automation to improve financial and regulatory workflows.

Lead design, development, and optimization of ETL/ELT pipelines and data products for telematics and third-party data. Ingest large-scale datasets into the enterprise data lake/lakehouse, implement CI/CD and DataOps practices, orchestration (MWAA/Autosys/Control-M), observability, and resilient self-healing pipelines. Mentor team members, collaborate with architects, data scientists, and BI teams, run POCs, and apply RAG and AI-driven systems while ensuring governance, security, performance, and data quality.

Design, build, and maintain scalable semantic 360 data models and transformation pipelines. Implement cleansing, enrichment, business rules, KPIs, and scoring algorithms using SQL and Python/Scala. Employ AI coding assistants and modern AI engineering practices to accelerate development while ensuring traceability, data quality, performance, and alignment with product and analytics needs.

Lead Data Engineer/ETL role requiring 5-10 years of Informatica ETL experience. Responsibilities focus on BDM, TDM, data quality, big data, data warehousing, and star schema design. Strong verbal and written communication and a technical bachelor’s degree required. Unix experience is a plus.

Design, build, and optimize SQL Server-based data layers and Azure data solutions. Own query performance, indexing, concurrency, CDC pipelines, ORM data access patterns (C#), and database CI/CD. Partner with engineers and architects, mentor team members, and ensure scalable, low-latency data platforms.

Hands-on data and integration engineer responsible for building, supporting, and automating Canoe-related workflows and integrations. Develop and maintain data pipelines, SQL queries, validations, reconciliations, and monitoring to deliver alternative investment data to Snowflake, Addepar, reporting tools, and downstream systems. Troubleshoot data quality issues, support production feeds, manage exceptions, document mappings and runbooks, and collaborate with investment, reporting, technology, and vendor teams. Hybrid role requiring Baltimore office presence three days per week.

Designs and implements scalable real-time and batch data pipelines, optimizes performance and reliability, applies ML libraries and quantitative methods, builds cloud-native AWS data platform components, develops CI/CD and orchestration, performs testing/validation and documentation, and collaborates on data-centric initiatives in a financial services environment.

Build, maintain, and optimize cloud data pipelines and dbt models; design Airflow DAGs; implement dimensional models and BI dashboards; integrate healthcare data with HIPAA-compliant practices; contribute to RAG pipelines and MLOps workflows; review contractor code, monitor data quality, and document designs following governance standards.

The Senior Data Engineer will design and maintain data pipelines, ensuring data reliability and consistent models, while collaborating with stakeholders to improve data practices.

As a Senior Data Engineer, you will design and optimize data pipelines, enhance system efficiency, and collaborate with teams to drive health outcomes using large healthcare datasets.

You will build and operate a validated data platform, ensuring data integrity, mentoring team members, and collaborating on data discoverability and queryability.

As a Senior Data Engineer, you will enhance the data lakehouse, optimize data workloads, perform complex transformations, and develop frameworks to improve delivery velocity, focusing on cybersecurity solutions.

Design and optimize data pipelines, automate ingestion frameworks, and enhance data layers within GCP for healthcare analytics and reporting.

The Lead Data Engineer will design and optimize scalable data pipelines within GCP for healthcare analytics and reporting, lead automation efforts, and mentor junior engineers.

The Senior Data Engineer II will build and optimize data solutions on Axon's Corporate Data Platform, design data pipelines, mentor team members, and uphold data governance and quality standards.

Design, build, and optimize scalable data ingestion and transformation pipelines in a medallion (Bronze/Silver/Gold) architecture on Microsoft Fabric/OneLake. Ensure HIPAA-compliant, multi-tenant data isolation, data quality monitoring, lineage and governance. Partner with Data Science, ML Engineering, and Software Engineering to deliver feature stores, ML-ready datasets, and production-grade data delivery for analytics and scoring.

Design, build, test, and maintain high-quality data pipelines and storage systems. Collaborate with architects, analysts, scientists to ingest, transform, and prepare data for analytics and ML, implement DevOps best practices, write tests and documentation, and improve data reliability, performance, and security using modern cloud and big-data technologies.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Lead design and implementation of scalable data architectures and pipelines for real-time and batch processing; mentor junior engineers; ensure pipeline reliability, monitoring, security, and governance; collaborate with cross-functional teams and adopt new data technologies.

Lead the data engineering team to design, build, and scale data platforms and pipelines. Set standards, manage projects and technical debt, collaborate with stakeholders, drive adoption of new tools, ensure data governance, and provide technical leadership for complex data issues and real-time architectures.