Top Data Engineer Jobs

Develop, implement, and maintain enterprise ETL pipelines and scalable data solutions. Optimize SQL and database processes, validate data, automate routine tasks, and collaborate with global teams to deliver accurate, timely data for Test & Learn products.

Design, build, and maintain cloud-based data pipelines and products (batch and streaming). Develop microservices, orchestration, and feature stores in AWS. Partner with stakeholders, automate ETL, enable self-service analytics, and mentor junior engineers.

The Geospatial Data Engineer designs and implements data architectures and systems for intelligence analysis, supporting GEOINT analysts with automation and model creation.

The Data Engineer will build datasets and pipelines for marketing and sales reporting, collaborating with various teams to support data needs and ensure scalable solutions.

Design, build, and maintain scalable cloud-native data pipelines and ETL/ELT solutions using Python/PySpark, Databricks, DBT and AWS/Azure services. Collaborate with architects, data scientists, and product teams to optimize data models, ensure data quality, monitor pipeline performance, and drive architectural improvements and automation.

Design and deliver enterprise-scale data models and analytics-ready datasets in Snowflake; build reliable ELT/ETL pipelines (batch and near-real-time); implement data quality, observability, and performance optimizations; publish curated data to downstream systems; enforce documentation, lineage, schema evolution, and secure handling of sensitive data while collaborating with product, operations, and engineering teams.

Design, build, and maintain data pipelines and tooling; collaborate with cross-functional stakeholders to deliver governed, high-quality datasets; own data quality and drive adoption of produced datasets.

The Data Engineer Co-op will work on web data feeds, utilize AI technologies and frameworks, and develop data pipelines.

The Data Engineer will architect and deploy Big Data environments, manage data pipelines, and ensure data integrity across the organization.

Lead design and implementation of ETL/ELT pipelines and database migrations into Databricks; model and optimize Lakehouse/data warehouse structures; ensure data quality, security, and observability; collaborate with cross-functional stakeholders and document data flows for analytics readiness.

Design, build, and test cloud-based data pipelines, warehouses, and integrations (ETL/APIs) for claims analytics. Work in an agile squad to ingest, curate, provision, and deploy data solutions using Snowflake, AWS, Data Vault, and related tools while mentoring junior engineers and ensuring CI/CD and data quality.

Design, build, test, and deploy cloud-based data pipelines, ETL, and data warehouse solutions (Snowflake) to support reporting, analytics, and data science. Collaborate in agile squads, perform code reviews, improve data quality and reliability, mentor junior engineers, and deliver production-ready data provisioning workflows.

Design, build, test, and deploy cloud-based data pipelines, warehouses, and ETL/API integrations (Snowflake, AWS). Collaborate in agile squads, mentor junior developers, ensure data quality, and support analytics and reporting solutions.

Design, build, test, and deploy cloud-based data pipelines and data warehouse solutions (Snowflake, AWS). Integrate Guidewire and enterprise sources, improve data quality, mentor junior engineers, and collaborate in agile squads to deliver analytics and reporting capabilities.

Design, develop, test, and deploy cloud-based data pipelines and warehousing solutions (Snowflake, AWS). Build ETL/API integrations (Guidewire), apply Data Vault methodology, ensure data quality, mentor junior engineers, and collaborate in agile squads to deliver analytics and reporting solutions.

Design, build, and maintain scalable ETL/ELT pipelines using Python, Spark, Databricks, Airflow and SSIS. Integrate and cleanse diverse healthcare datasets, implement Unity Catalog for metadata and governance, optimize Spark performance and JVM tuning, support Medallion architecture, and collaborate with cross-functional teams to automate CI/CD, observability, and data quality processes.

As a Data Engineer, you will design and maintain data pipelines, build data storage systems, and support analytics workflows, ensuring data reliability and performance. You will collaborate with engineers to define data structures and improve data management practices.

As a Data Engineering Intern, you will contribute to data products, manage automation tools, help develop Infrastructure as Code, and optimize and support data processes while collaborating with the engineering team.

The Data Engineer develops, programs, and integrates data solutions, analyzes diverse datasets, and collaborates with business units to drive solutions.

The Data Engineer will support data initiatives, build data pipelines, perform statistical analyses, and develop BI dashboards to drive business decisions.

You will design and optimize cloud-based data pipelines in AWS, develop automation frameworks, and enhance data architecture for financial reporting and actuarial modeling.

The Data Engineer will design and build scalable data systems, support AI/ML integration, and collaborate across teams for the development of Canoe's Alts Data Platform.

Lead design and build of a scalable, secure cross-cloud data platform and marts. Drive selection and optimization of the modern data stack, enforce governance and lineage, and establish reusable data models and best practices to support analytics, BI, and ML use cases across product and engineering teams.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

The Senior Research Engineer will curate large datasets, automate data pipelines, optimize queries, and support data-driven research impacting business outcomes.