Top Data Engineer Jobs

The Senior Data & Analytics Engineer will design and maintain data pipelines, develop analytics schemas, build visualizations, and perform deep-dive analyses to drive business decisions.

As a Senior Data Engineer at First American, you will enhance data security processes, manage projects, generate reports, and collaborate with teams to secure data assets.

As a Senior Data Engineer, you will collaborate to build Data Warehouse Solutions, develop data products, and optimize data processes using tools like dbt and Airflow. You'll ensure data integrity and work with various stakeholders to translate business requirements into technical solutions.

Design and implement real-time and batch data pipelines (MQTT/Redpanda, Dagster), parse binary message formats, build data warehouses (Postgres, Iceberg, Parquet, S3), design high-performance data models, validate and normalize sources, and improve local development and CI/CD with GitHub Actions to support maritime domain awareness and defense-related AI workloads.

The Senior Data Engineer will design, develop, and support data solutions, working with extensive cloud and data technologies while collaborating with Agile teams.

As a Data Platform Engineer, you'll design and maintain scalable data systems, partner with teams on product direction, and ensure system reliability and security.

Lead design, build, and deploy end-to-end data and ML pipelines for imagery models. Partner with Data Science and stakeholders to prioritize use cases, integrate models into production and APIs, implement monitoring, enforce data governance and quality, define reusable frameworks, and provide technical leadership and mentoring across teams.

Lead architecture, strategy, and hands-on execution for Faire's data platform. Build and scale secure, cost-efficient data ingestion, ETL/ELT, warehousing, orchestration, monitoring, and governance. Mentor engineers, influence cross-team priorities, and drive performance and cost optimization for analytics and data products.

Ensure timely, high-quality data conversions from legacy systems to new platforms. Work with Implementation Specialists and Project Managers to execute conversion tasks, validate data integrity, troubleshoot issues, support deployments, and assist scheduling and customer communications.

Build and automate zero-config ingestion pipelines for major marketing and CRM platforms, transform third-party JSON into analytical schemas, map event data into unified identity/event streams, and integrate Martech data into the core ClickHouse/ML environment.

Lead design and delivery of large data products and pipelines, mentor senior engineers, set standards and best practices, promote data/analytics across business units, collaborate on governance and curated data catalog, and present technical work externally.

Architect and scale cloud data platforms and ETL/ELT pipelines (batch and near-real-time), ensure data quality and observability, implement CI/CD for data infrastructure, collaborate with stakeholders and mentor junior engineers to deliver analytics and machine-learning-ready data products.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Design, build, and own robust batch and real-time data pipelines and golden datasets using SQL and Python. Ensure data quality, performance, schema design, and SLAs while partnering across engineering, product, and business teams. Advocate tooling and best practices, document datasets, and deliver reliable analytics infrastructure at petabyte scale.

Lead design and delivery of Databricks-based Lakehouse solutions and end-to-end data engineering projects. Build and optimize ETL, streaming and batch pipelines, integrate cloud and on-prem systems, mentor team members, support pre-sales, and ensure governance, security, and platform performance.

Lead ownership of data infrastructure and ETL: design, build, and maintain Airflow pipelines ingesting from Postgres and SaaS sources; optimize Snowflake/BigQuery warehouses and dbt transformations; drive architecture, mentor teammates, and align data platform roadmap with business needs.

Lead design and implementation of scalable batch and streaming data infrastructure. Build and maintain ETL/ELT pipelines, ensure data quality and observability, troubleshoot production issues, mentor engineers, and partner with cross-functional teams to deliver reliable, self-serve data products.

Lead design and implementation of scalable data architectures and pipelines (real-time and batch), mentor junior engineers, ensure pipeline reliability and security, adopt new tools, collaborate cross-functionally, and implement data governance.

The Senior Data Engineer will design and maintain data architectures, work with operations teams, solve complex data challenges, and document decisions for stakeholders.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

Lead design and implementation of scalable ETL/ELT pipelines and Snowflake data models. Optimize workflows, ensure data quality and observability, support BI (Tableau, Domo, Power BI), mentor engineers, and drive data platform architecture and roadmap.

The role involves building data pipelines, developing machine learning models, and improving actuarial and finance functions, collaborating with various teams.

Design, build, and operate a scalable, resilient Data Lakehouse. Lead architecture, evaluate open-source tooling, ensure performance and usability, mentor engineers, collaborate across teams, and drive DevOps and cloud best practices.

Founding technical leader for the data platform: build and operate ingestion, enrichment, batch and realtime pipelines; design storage, modeling, and governance; integrate LLM/ML workflows and vector search; hire and lead a small data team; and collaborate with engineering, product, and leadership to productionize data for valuations, analytics, and APIs.

Design and build Spark ETL pipelines on an AWS data platform, collaborate with stakeholders to deliver reliable large-scale data products, optimize and maintain data infrastructure, ensure data quality/governance, and manage platform operations and incident response.