Top Remote Data Engineer Jobs

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

Build and maintain cloud data pipelines and ML feature/model workflows in Snowflake and AWS. Implement data ingestion, transformations, quality checks, monitoring, and documentation. Collaborate with data scientists, analysts, and product teams to support analytics, audience insights, rapid prototyping, and reliable production deployments.

Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.

Design and maintain ETL pipelines and graph data models to ingest security telemetry into an AWS Neptune knowledge graph, enable ML-driven threat detection, optimize query performance, ensure data quality and compliance, and document workflows.

The Senior Quantitative Data Engineer will build and maintain scalable data pipelines for quantitative investment research, ensuring data integrity and compliance, while collaborating with various teams for data architecture and product strategy.

Lead and mentor multiple Databricks-focused data engineering teams, define engineering best practices and reusable frameworks, drive CI/CD and performance/cost optimization, build and support analytical and streaming pipelines, and collaborate with architects, product owners, and cross-functional partners to deliver high-quality data products.

Design, build, and maintain large-scale data pipelines using Microsoft Fabric and Databricks. Develop data architectures, ensure data quality and governance, optimize processing and storage, integrate with ML and analytics, implement monitoring, and collaborate with Product and Engineering to prioritize data initiatives.

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 ETL/data pipelines and storage (data lakes, warehouses) on AWS. Implement real-time streaming, data modeling, cleansing, security, and Data Mesh architectures. Collaborate with data scientists and mentor junior engineers to deliver high-quality, large-scale data solutions.

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.

Transform raw engineering data into high-fidelity datasets for AI: ingest, clean, label, and create CAD reference models and engineering artifacts, build annotation workflows and tooling, collaborate with product/research/engineering/customer teams, and ensure dataset quality and manufacturability considerations for model training and evaluation.

The Data Engineer will develop and optimize data pipelines, manage data architecture, support cross-functional teams, and ensure data security and integrity.

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.

As a Staff Data Engineer, you'll architect and model data, create ETL pipelines, and standardize datasets for compliance teams. You'll guide best practices and lead data solutions while collaborating with various stakeholders.

The Data Engineer will build ETL pipelines and data infrastructure, ensure data quality, and implement modern data warehousing for analytics improvements, while collaborating with stakeholders across teams.

The Data Engineer will manage data ingestion in Salesforce, standardize lead data, ensure data quality, and optimize integration workflows.

The Data Engineer will build scalable privacy-centric data frameworks, engineer data pipelines, and ensure compliance with privacy regulations at Netflix.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

Lead and mentor a data engineering team to design and operate scalable ETL/ELT pipelines and Snowflake data warehouse solutions using Python, DBT, Matillion, and AI tools; establish standards, ensure data quality and governance, and collaborate with analytics, product, and BI stakeholders to deliver production-ready data platforms.

The Senior Data Engineer at Unchained will design and implement data pipelines, integrate APIs, ensure data governance, and mentor team members while focusing on accuracy and security.

As a Senior Data Engineer, you will design data pipelines, manage databases, optimize data workflows, ensure data integrity, and collaborate with cross-functional teams on data-driven solutions.

Responsible for building scalable data pipelines, transforming data using Python and SQL, and collaborating with teams to ensure data quality and successful analytics solutions.