Top Senior Data Engineer Jobs

Design, implement, and maintain cloud-based data pipelines and warehousing/lake solutions. Advise clients on best practices, lead technical decisions, mentor engineers, and collaborate with stakeholders to deliver scalable, maintainable data engineering solutions.

Design, implement, and maintain cloud-based data pipelines and platforms. Advise clients on best practices, integrate disparate data sources, optimize data warehousing/lake solutions, mentor engineers, and ensure scalable, maintainable data architectures across cloud environments.

Designs, builds, and deploys data pipelines and integrations to support analytics and machine learning for digital pathology. Partners with product owners and ML teams to extract, transform, validate, and visualize data, enabling insights and model development. Maintains platform knowledge and provides consultative support across teams.

Lead teams to design, build, and operate scalable, AI-ready data pipelines and ecommerce data products (especially Shopify). Build semantic layers, curated data marts, and data models; ensure data quality, monitoring, and performance. Collaborate with data scientists, analysts, and governance to support feature engineering, ML datasets, and reliable downstream consumption.

Lead design and evolution of a company-wide data platform spanning streaming, batch, warehousing, orchestration, governance, and ML enablement. Deliver core platform capabilities, reliable real-time pipelines, shared tooling, and scalable infrastructure. Drive cross-team initiatives, champion golden paths, improve reliability/cost/observability, ensure regulatory compliance, and mentor senior engineers while influencing technical strategy and standards.

Build and scale optimized data pipelines and data engine architecture to run ML models, reduce annotation costs, integrate foundation models for labeling and QA, use software/hardware-in-the-loop testing, and collaborate with DoD customers to understand requirements and support field events.

Own design, build, and reliability of a cloud-native data lakehouse (Bronze->Silver->Gold). Build scalable ETL/ELT pipelines (ADF, Airflow), optimise Snowflake, develop dbt models, embed data quality/observability (Elementary), manage ADLS Gen2 and Azure serverless components, and drive infra-as-code, CI/CD, and cross-team collaboration.

The Senior Data Engineer will build and maintain data pipelines, distributed ETL/ELT workflows, and data storage systems while collaborating with various teams to optimize data quality and performance.

Design, build, and optimize scalable ETL/ELT pipelines and cloud data platforms. Integrate data from SQL Server, Yardi, Salesforce and APIs into AWS (S3, Redshift). Collaborate with analytics, data science, and business teams to deliver trusted datasets, ensure data quality and governance, and implement DevOps, CI/CD, and infrastructure automation for operational excellence.

Design, build, and operate Brex's data enablement platform (warehouse, streaming, replication, orchestration, observability, governance). Partner with product, data science, and analytics teams to deliver data-backed products, improve data competency, and maintain resilient, on-call data architectures.

Own ingestion, transformation, validation, and normalization of clinical and EHR data pipelines (HL7 v2, FHIR, CDC) into performant Snowflake and MySQL schemas. Build and monitor AWS-based pipelines, ensure data quality and PHI-compliant handling, and support downstream ML and application needs across enterprise integrations.

Lead design and implementation of scalable Databricks ETL/ELT pipelines and data architectures for marketing analytics, manage 1-2 projects, liaise with stakeholders, ensure data quality, monitoring, and delivery of analytics-ready datasets.

Design, build, and maintain scalable ETL/ELT pipelines, data warehouses, and data lakes. Ensure data quality, governance, and security while enabling BI and analytics. Provide technical leadership, mentor junior engineers, and collaborate cross-functionally to drive architecture and implementation.

Design, build, and maintain scalable real-time and batch data pipelines and platform architecture. Ensure data quality, enable BI/AI/ML productionization, mentor engineers, and deploy data products and ML models.

Lead a team of data engineers to design, build, and maintain scalable data pipelines, a Data Vault, data warehouses and marts. Own backlog, sprint planning, mentoring, stakeholder collaboration, data validation/monitoring, and platform improvements to deliver key metrics and data infrastructure across the business.

Own and modernize the legacy SQL data estate: support and stabilize SQL Server databases, build and modernize ELT pipelines (including SAP integration), create analytics-ready data models, ensure HA/DR and recovery objectives, and operationalize data governance and privacy (GDPR/CCPA). Serve BI, reporting, and AI consumers while partnering with architecture, DBA, and GRC teams.

Build and maintain enterprise data platform and ETL/ELT pipelines, design and deploy data models, ensure data quality and governance, integrate third-party sources, and support analytics and AI initiatives across the organization.

Design, develop, and maintain enterprise ETL pipelines and scalable data processing using ADF, Informatica, Python, Spark/Databricks, and relational systems. Support Medicaid analytics, data validation, cloud migrations, production operations, and CI/CD practices.

Design, build, and maintain a petabyte-scale open-source data lakehouse and end-to-end data pipelines (ingest → transform → consume) ensuring performance, reliability, and data quality for analytics workloads.

Design and own end-to-end data platform architecture, build ingestion and transformation pipelines, model multi-tenant datasets, optimize Postgres and ClickHouse performance/cost, implement orchestration and observability, define data quality and reconciliation standards, and mentor data/product engineers.

Own and modernize the legacy SQL data estate: support and stabilize SQL Server databases, design HA/DR and recovery plans, build resilient ELT pipelines from sources including SAP, create analytics-ready data models for BI/AI, operationalize data governance and privacy (GDPR/CCPA), and mentor DBA succession while delivering documentation and runbooks.

Build and operate production data infrastructure: ingest, transform, and route large-scale streaming and batch data from heterogeneous enterprise sources; design ontology/semantic models and tuple/graph representations; ensure isolation, data quality, observability, and low-latency delivery for ML and product teams.

Design, build and scale a 500+ TB Audience Management Big Data platform. Own data ingestion, validation, transformation and storage pipelines. Write server-side Spark/Scala code, perform R&D on new technologies, mentor engineers, and partner with product managers to meet roadmap and business needs.

Lead design and implement scalable data infrastructure and transformations. Build data repositories, convert data science algorithms into robust pipelines, mentor a small data engineering team, ensure delivery quality, and collaborate with Product, Data Analysts, and Data Scientists.

Design and implement scalable data infrastructure and production data transformations. Lead and mentor a small Data Engineering team, ensure quality delivery, collaborate with Product, Data Analysts, and Data Scientists to operationalize algorithms and build robust data repositories.