Top Senior Data Engineer Jobs

As a Senior Data Engineer, you will build data pipelines, improve the data engineering stack, and maintain a data warehouse for analytics. You'll collaborate with teams to ensure data accuracy and contribute to system reliability.

Lead design and implementation of scalable multimodal data pipelines, active learning and labeling loops, training and inference engineering, and model serving/optimization. Focus on data cleaning, OCR/layout normalization, sample construction, observability, and cost-efficient multi-model routing.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

Lead design and build scalable ETL pipelines and data models to support technology cost, usage, and finance insights. Partner with stakeholders, optimize performance, automate workflows, ensure data quality/governance, and mentor junior engineers.

Lead design, build, and scale of data platform capabilities across Snowflake and AWS. Develop ETL/ELT pipelines, CI/CD and IaC, monitoring, and governance. Mentor engineers, collaborate cross-functionally, and ensure security and compliance (SOC2, PCI-DSS).

Design, build, and maintain production data pipelines and the unified data model using Snowflake, dbt, and orchestration tools. Optimize, test, document, and monitor ELT workflows, enforce engineering best practices, mentor teammates, and deliver trustworthy data products for analytics and business decisions.

Architect, build, and maintain scalable ELT data pipelines and analytics-ready data marts. Lead dbt modeling, ensure data quality, CI/CD, and documentation. Partner with stakeholders, mentor junior engineers, evaluate tooling (reverse ETL), and drive long-term data platform strategy.

Design, build, and maintain production data pipelines and tooling (CI/CD, testing, validation) using Snowflake, dbt, and orchestration tools. Model, transform, document, and optimize data to produce reliable curated datasets for analytics and solutions, enforce engineering best practices, and mentor teammates while ensuring scalability, observability, and data integrity.

Design, build, and maintain scalable cloud-native ETL/ELT pipelines and serverless workflows using Python, Airflow, and AWS. Implement dbt transformations, manage DynamoDB and other storage, enforce data quality and governance, automate CI/CD, and mentor junior engineers while collaborating with analytics, product, and creative teams.

Lead design, build, and support of cloud-based ETL, data warehousing, and reporting solutions. Develop/optimize ETL pipelines, data models, and queries; deploy containerized services on Kubernetes; automate workflows; mentor teammates; collaborate with architects, data scientists, and stakeholders to deliver scalable analytics and reporting products.

The Senior Data Engineer will manage end-to-end data processes, develop ETL/ELT pipelines, and provide analytics-ready outputs using Python, Azure, and Snowflake.

The Principal Data Analytics Engineer will design complex data models, optimize querying processes, mentor team members, and ensure data quality across financial datasets.

Design and operate petabyte-scale data infrastructure: build high-throughput streaming pipelines, architect a tiered Data Lakehouse, automate orchestration and backfills, optimize embedded team data schemas, manage Kubernetes stateful deployments, and enforce data quality, governance, and access controls.

Design, build, and scale data pipelines and integrations for the TDX platform. Implement REST API integrations, ingest and unify customer data, optimize pipelines for performance and quality, ensure data security and governance, and collaborate with Product, Data Science, and customer teams to deliver reliable analytics-ready data.

Lead architecture and scaling of Databricks/Azure data platform, design integration patterns (APIs, event-driven, HL7/FHIR), build high-performance ETL/ELT pipelines in Python/SQL, enforce governance/security (Unity Catalog, HIPAA/SOC2), and mentor engineering teams.

Design and maintain ELT pipelines, build dimensional (star/snowflake) analytics models, implement data transformations and quality checks, document data lineage and governance, partner with BI users, and mentor junior engineers to deliver performant analytics for business reporting and KPIs.

Design and maintain scalable data pipelines, ensuring accurate delivery and governance of data across the organization while collaborating with cross-functional teams.

Lead design and implementation of batch and streaming data pipelines, build data models, implement data quality and testing, manage orchestration and IaC, mentor engineers, and communicate technical direction and tradeoffs to stakeholders.

Lead design and optimization of enterprise Snowflake data warehouses, build scalable Python data pipelines, implement IaC on AWS, enforce data security, drive DataOps/CI-CD, and collaborate across agile teams to support mortgage analytics and financial systems.

Lead design and evolve cloud-native database and data access architectures, set data engineering standards, lead integrations and cross-functional projects, mentor engineers, and drive operational excellence, monitoring, resilience, and GenAI-assisted automation.

As a Senior Data Engineer, you will build complex data solutions and pipelines, support analytics growth, and educate users. Collaboration and advanced technical skills are essential.

Design, build, and maintain scalable data pipelines and platform tools; define canonical data models; deploy and operate workflow managers (Airflow/Jenkins); work with cloud data tools (Redshift, EMR) and infra (Kubernetes, Terraform); implement data security controls; mentor junior engineers and collaborate with data scientists, analysts, and product teams.

The Senior Data Engineer leads data engineering efforts, coordinating project execution and collaborating with teams to develop data solutions for Navy and DoD programs.