Top Remote Data Engineer Jobs

Maintain data integrity and quality through advanced testing and validation of ETL pipelines. Analyze complex data issues, build solutions, mentor junior staff, engage with clients, and support continuous improvement across data management, governance, and pipeline orchestration.

As the first in-house Data Engineer, you will own the data infrastructure, build and maintain data pipelines, and collaborate with teams to ensure quality data access and insights.

Lead architecture and implementation of scalable data pipelines, integrations, and cloud data infrastructure. Own IaC (Terraform), workflow orchestration (near-real-time and batch), third-party API and AI/LLM integrations, data export pipelines, and internal tooling. Mentor engineers, drive technical strategy and cross-team priorities, and communicate tradeoffs to technical and non-technical stakeholders. Must work EST/CST hours and be authorized to work in the US.

As a Senior Data Engineer at Jellyfish, you'll build and maintain data pipelines, optimize orchestration, automate CI/CD processes, and enhance data integration while ensuring high performance and reliability.

Design, build, and optimize scalable data pipelines and ETL/ELT processes on cloud-native platforms (Databricks, Informatica). Implement Data Lakehouse models, ensure data quality, support CI/CD deployments, monitor production workflows, and enforce governance, security, and compliance for healthcare data alongside architects and stakeholders.

Senior Databricks data engineer supporting Azure-based analytics modernization for a federal emergency management platform. Build and optimize ETL pipelines, Delta Lake/Delta Sharing integrations, data lakes/warehouses, and feature stores; prepare data for ML/MLOps; ensure data quality and security; engage stakeholders and external partners; mentor junior staff and work in Agile teams to deliver scalable data products.

The Palantir Data Engineer will design and maintain ontologies, implement data pipelines, and ensure data integrity while collaborating with product owners and teams.

Design, build, and maintain scalable data pipelines and ETL processes in Azure (Synapse, Data Factory). Integrate data via APIs, ensure data quality/security, support analytics and Power BI reporting, collaborate with stakeholders, and manage work using Agile/Jira to support federal healthcare and VA initiatives.

The Associate Data Engineer I role involves supporting data pipeline development, troubleshooting data issues, and collaborating with engineers and analysts using SQL and Python.

Design, build, test, and maintain APIs and integration flows across cloud, on‑prem, and third‑party systems. Implement synchronous/asynchronous and event‑driven patterns, troubleshoot production issues, support QA and CI/CD, document solutions, and collaborate with stakeholders to deliver scalable, secure integration components.

The Data Engineer designs and maintains scalable data solutions, builds data pipelines, ensures data quality, and collaborates with teams to support analytics.

Design, build, and maintain scalable Spark-based ETL pipelines and computed tables in a central data lake. Integrate structured and unstructured IoT, sensor, and external data for analytics, model training, and dashboards. Collaborate with Data Science, Analytics, and ML teams to ensure reliable, high-quality customer-facing datasets.

Build and maintain ETL/ELT pipelines, ingest and transform structured and unstructured data, integrate APIs and external sources, improve data quality and monitoring, support dashboards and ML pipelines, optimize warehouse and cloud performance, and contribute to data governance and documentation.

Design, build, and maintain production-grade ETL/ELT pipelines and data models using dbt, Spark, and cloud platforms. Manage ingestion, data quality, observability, semantic layers, and BI outputs. Collaborate with analysts and data scientists to deliver governed, high-quality data products and implement DataOps and CI/CD practices.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

The Data Engineer will build and optimize data pipelines and cloud solutions, collaborating with teams to ensure data quality and leveraging modern engineering tools.

As a Data Engineer, you will build and optimize data pipelines, ensuring accurate data delivery that informs pricing and market analytics at Alt.

The Senior Bioinformatics Data Engineer will build data pipelines, implement clinical data ingestion, and optimize platform infrastructure while ensuring data quality and compliance with legal standards.

Lead design, build, and optimize scalable ETL/ELT data pipelines and analytics platforms using Databricks and Spark. Integrate and transform source data into analytics-ready layers, maintain data documentation and lineage, optimize SQL Server performance, collaborate with product and engineering teams, and apply AI-enabled tools responsibly to drive business insights.

Provide senior-level data engineering for analytics: resolve complex technical issues, build decision-support reports and dashboards, lead projects, prepare and integrate data, coach staff, and ensure high-quality analytics to support academic, research, and healthcare goals.

Design, implement, and maintain scalable data pipelines and storage for intelligence operations. Build ETL and real-time ingestion, optimize queries and data models, enforce data quality, governance, and security per IC standards, and collaborate with analysts and mission partners.

As an ETL Data Engineer, you'll design and maintain data integration processes using Python and Azure Synapse Analytics, ensuring data accuracy for insights. You'll collaborate with teams, implement data quality checks, and contribute to performance tuning and data modeling.

The Azure Data Engineer will design and develop ETL processes, utilizing Python and Azure Synapse Analytics, to manage data integration and ensure data accuracy. Responsibilities include performance tuning, data modeling, and collaboration across teams.

Design, develop, and secure database systems that integrate structured and unstructured data from diverse sources. Build ETL processes, SQL/PLSQL/T-SQL routines, Oracle APEX web apps, and Power BI reporting to enable data mining, quality checks, and analytics for engineering and materials data.

The Data Engineer will design and implement data architecture, develop data ingestion pipelines, collaborate with stakeholders, and improve data-related processes.