Top Remote Data Engineer Jobs

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.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

As a Data Engineer II, you will build and optimize data pipelines in Databricks, ensure high-quality data delivery, and support generative AI applications. You will collaborate with data scientists and AI engineers to provide reliable data infrastructures and meet business needs.

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.

The Senior Data Engineer handles ChowNow's data platform, collaborating with teams to enhance data availability and insights, supporting internal and customer-facing products.

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.

We're seeking a Data Engineer with 5+ years of experience to build data processing solutions using Python, design data models, and process large data streams while ensuring high performance across various data technologies.

Lead the engineering and operational excellence of data collaboration ecosystems, focusing on scalable data architectures, automation, and MLOps practices.

As a Senior Data Engineer, you will enhance data products, build automated data pipelines, and improve data platform capabilities, collaborating with various teams to drive initiatives.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

The AWS Data Engineer will design, build, and optimize data pipelines on AWS, ensuring performance and data quality for analytics. Responsibilities include developing ETL processes, collaborating with teams, and monitoring data workflows.

This role involves building and maintaining data pipelines, developing data models, and ensuring data discoverability while enabling scalable analytics on blockchain data.

Design, build, and maintain scalable data models, ETL/ELT pipelines, and architecture for healthcare datasets. Ensure data quality, governance, security (HIPAA/SOC2/HITRUST), and support analytics and GenAI use cases while collaborating with Data Science and engineering teams.

The Data Engineer will design and implement scalable data platforms, build data pipelines, collaborate with teams to ensure data quality, and streamline processes using AWS services and big data technologies.

Design, build, and validate pipelines to ingest, standardize, and publish real-world healthcare datasets (claims, EMR, registry). Perform SQL, Python, and SAS transformations, OMOP conversions, QA, and vendor communications to deliver high-quality datasets for analytics and research.

The Data Engineer designs and maintains scalable data infrastructure to support enterprise products, ensuring efficient data ingestion, transformation, and delivery across systems while collaborating with cross-functional teams.

The Data Engineer at Netflix builds systems for efficient data processing and modeling, collaborating with various teams to empower analytical insights and product features.

Design, build, and maintain Databricks-based data warehouse and lakehouse solutions for healthcare data. Implement ETL/streaming pipelines, data governance, security (PHI/PII), Infrastructure-as-Code, cost optimization, and pipeline monitoring while collaborating with cross-functional teams to deliver reliable data products.

Design, build, and maintain scalable, reliable data pipelines and services. Write well-tested Python and SQL code, work with orchestration (Airflow), containers, and cloud infrastructure. Collaborate cross-functionally to deliver data products and improve development processes.

Build and maintain Databricks-based ETL/ELT pipelines, transform and model data, optimize workflows, monitor and troubleshoot pipelines, and collaborate with cross-functional teams.

The role involves managing data infrastructure, building data pipelines, providing analytics to inform business decisions, and shaping AI workflows in the organization.

The Specialist, Data Engineering will design and develop data solutions, integrate data sources, and build data pipelines to support analytics and product offerings.

As a Data Engineer, you will develop data pipelines, optimize processes, integrate data sources, and improve data platform architecture while collaborating across teams.

The Principal Data Engineer will design and implement enterprise data frameworks, mentor teams, and ensure data quality while collaborating with stakeholders.

The Data Engineer I will manage data warehouses, extend data pipelines, write SQL and Python scripts, and support data operations.