Top Senior Data Engineer Jobs

Design and develop scalable data architectures and pipelines across on-prem, cloud, and hybrid platforms. Build data warehouse and analytics solutions, perform data wrangling and discovery, mentor engineers, and assist in project planning and estimation to enable data-driven business insights.

Manage and develop data systems and architectures for the NC3 digital environment; perform ETL in cloud environments, build and query relational/non-relational databases, conduct advanced analytics and modeling, develop dashboards and data quality tools, and support DoD interoperability and data strategy.

Design and build scalable data pipelines for Investment Data Standard and knowledge graph, implementing data quality controls and collaborating with cross-functional teams.

Design, build, and optimize low-latency streaming analytics pipelines; develop time-series models, real-time APIs and visualizations; operationalize online ML inference and monitoring; deploy services with Docker/Kubernetes on cloud; implement observability, governance, and mentor engineering teams.

Lead Data Engineer partners with product, architecture, and engineering to design, build, and operate scalable data solutions. Responsibilities include translating product requirements into data designs, building ETL/ELT pipelines, optimizing data storage and flow, implementing data cleansing and automation, ensuring data quality and compatibility, guiding architectural patterns, estimating project scope, and mentoring teams while staying current with emerging data technologies.

Build instrumentation and batch/streaming ETL/ELT pipelines and REST API integrations to generate audience and trigger data for CRM/marketing automation. Ensure data quality, monitoring, and reliability at scale while collaborating with CRM, campaign, and operations teams.

Design, build, and optimize scalable GCP data pipelines and ingestion frameworks, develop BigQuery semantic layers and ELT/ETL workflows, implement automation, observability, and CI/CD, support data governance and quality, mentor engineers, and partner with stakeholders to deliver enterprise healthcare analytics solutions.

Design, build, and operate large-scale Hadoop-based data pipelines and analytics platforms. Ingest, transform, and analyze massive structured and unstructured data to support enterprise analytics, machine learning, and reporting. Ensure reliable, performant, and cost-effective production data platforms.

Lead design and scaling of ELT pipelines and analytics schemas on Snowflake. Build Looker views, CI/CD automation, and orchestration workflows (Prefect/Airflow). Ensure production reliability with monitoring (Datadog, Monte Carlo), partner with cross-functional teams, and provide technical leadership including code reviews, testing, and end-to-end ownership of data integrity and platform trustworthiness.

Design, build, and operate large-scale Hadoop-based data pipelines and analytics platforms. Ingest, transform, and analyze structured and unstructured data to support analytics, ML, and reporting. Implement streaming solutions, workflow orchestration, and ensure reliable, performant, and cost-effective production data platforms.

Design, build, and operate large-scale Hadoop-based data pipelines and analytics platforms. Ingest, transform, and analyze structured and unstructured data to support analytics, ML, and reporting. Ensure reliability, performance, and cost-effectiveness in production; troubleshoot, document, and collaborate on data engineering workflows.

Design, build, and operate large-scale batch and streaming ingestion pipelines, medallion/lakehouse layering, identity resolution and golden-record consolidation, data-quality gates and reconciliation, source-to-canonical mappings and crosswalks, schema enforcement, and observability for client onboarding and production data flows.

Lead the data platform team owning dbt projects, CI/CD, and Snowflake infrastructure. Architect scalable onboarding for new sources, enforce data quality via tests and contracts, review designs, prioritize roadmap, partner with stakeholders, and grow engineers while advancing AI/agent integration.

Lead telemetry and experimentation data engineering for Global Skilling products. Own instrumentation and telemetry contracts, build A/B testing pipelines and semantic models, integrate catalog/content data, deliver external reporting, operate insights feedback loops, mentor mid-level engineers, and provide on-call leadership for product-tier pipelines.

Design, build, and maintain large-scale data infrastructure and pipelines. Integrate data from multiple sources, ensure data quality and security, optimize performance, implement monitoring and governance, troubleshoot data issues, and collaborate with cross-functional teams to support analytics and BI workloads.

The Sr. Data Engineer will develop KPIs for infrastructure costs, analyze data, create reports, and enhance data systems for Starlink's ground network.

The Senior Data Engineer will build data pipelines and infrastructure, modernize legacy systems, and ensure data reliability for analytics at ABCorp.

Build and maintain scalable batch and streaming data pipelines on GCP, develop API-driven integrations, design data models, ensure data quality and performance, and deliver end-to-end solutions in a client-facing healthcare data environment.

Design, build, and maintain data pipelines and models for hardware manufacturing, device traceability, yield, and supply chain. Integrate MES/ERP/IoT data into a lakehouse, ensure end-to-end data quality, security, and governance, and partner with Hardware, Operations, and Quality teams. Support lakehouse architecture (Iceberg, Databricks, dbt) and reduce single-point-of-failure risk for manufacturing data.

Design, build, and maintain Scala-based ETL and streaming data pipelines, APIs, and data microservices in Azure. Optimize LLM fine-tuning and RAG workflows, support DevOps/CI-CD practices, document standards, mentor engineers, and manage data ingestion frameworks for analytics and partner integrations.

Design and implement scalable cloud data platforms and end-to-end ETL/ELT pipelines, migrate legacy infrastructure to Snowflake/AWS, optimize data warehouses, build transformations with dbt and Dagster orchestration, develop data processing with Python and SQL, implement IaC and CI/CD, and ensure data observability and governance while collaborating with stakeholders.

Design, build, and maintain enterprise data pipelines, stores, and microservices using big-data tools and cloud platforms. Collaborate with data scientists, modelers, and stakeholders to prepare, transform, and serve scalable, compliant data assets for analytics, reporting, and business decision-making.

The Senior Data Engineer will own the data pipelines, platform architecture, and data modeling for a cloud data warehouse, ensuring data integrity and usability for business functions like Finance and HR.

Design and build scalable data lakes, warehouses, and lakehouse architectures. Implement Python ETL/ELT pipelines and Airflow orchestration, ingest data from third-party APIs, optimize columnar formats and SQL, support ML initiatives, consult with stakeholders, and provision infrastructure using AWS, Snowflake, Spark, and Terraform.

The Principal Data Engineer will lead the design and development of scalable data platforms, optimize data pipelines, and collaborate with multiple teams to enhance data solutions.