Top Data Engineer Jobs

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.

Build and maintain scalable ETL pipelines and storage for multimodal clinical and NLP data; ensure data quality, security, and compliance; implement synthetic-data generation and real-time model evaluation infrastructure; create dashboards and documentation to support AI research and monitoring.

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.

Design, build, and test cloud-based ETL/data pipelines and data warehouse solutions (Snowflake, AWS). Collaborate in Agile squads to ingest, curate, provision data for analytics, ensure data quality, CI/CD, and automate data operations.

Design, build, and maintain cloud-based data pipelines, ETL processes, and data warehouse architectures (Data Vault, Snowflake) to support analytics, reporting, and ML. Collaborate in agile squads, implement CI/CD and automated testing, optimize data quality and performance, and troubleshoot production issues while advancing data engineering practices.

Design, build, and maintain cloud-based data pipelines, ETL, and data warehouse solutions (Snowflake, Teradata). Collaborate in agile squads to ingest, curate, and provision data for analytics and ML, implement CI/CD and automated testing, troubleshoot issues, and improve data quality and performance.

Design, build, and maintain cloud-based data pipelines, ETL, and data warehouse solutions. Implement Data Vault models, automate ingestion/curation, ensure CI/CD and automated testing, improve data quality, and support analytics and ML use cases while working in agile squads.

Design, build, and maintain cloud-based data pipelines, ETL processes, and data warehouse solutions (Data Vault, Snowflake) in an Agile team. Ensure data quality, CI/CD, automated testing, and production readiness while collaborating with product and engineering stakeholders to enable analytics and data science use cases.

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