Top Data Engineer Jobs

The Data Engineer will design and optimize ETL pipelines, integrate data, ensure data integrity, tune SQL queries, troubleshoot issues, and collaborate with teams to create data solutions.

Design and build scalable cloud-native data pipelines and models to produce trusted, analysis-ready data. Ensure data quality, governance, and privacy controls, apply software engineering best practices, enable BI and AI/ML consumption, and collaborate with clients and cross-functional teams.

The Senior Data Engineer will architect AI infrastructure, design high-performance data systems, manage AI pipelines, and collaborate with cross-functional teams. Responsibilities include implementing data architecture best practices and providing documentation and leadership in data orchestration.

The Staff Data Engineer will lead design and implementation of analytics platforms and data products, collaborate cross-functionally, mentor engineers, and drive best practices at Upside.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

Design, build, and operate scalable Spark-based ETL/ELT pipelines and data platforms on AWS. Manage end-to-end data lifecycle, ensure data quality and observability, optimize performance and costs, enforce CI/CD and IaC best practices, and collaborate with stakeholders to deliver production-grade analytics solutions.

The Data Engineer designs and maintains data pipelines for advanced analytics in supply chain, ensuring data quality and reliability while collaborating with cross-functional teams.

Lead the design and evolution of the enterprise data platform, establish standards, mentor teams, and collaborate across departments to deliver high-quality data products.

The Data Engineer is responsible for designing and developing cloud-native data pipelines, integrating machine learning models, and ensuring the reliability and scalability of data solutions in a collaborative environment.

As a Data Engineer, you will build and maintain data pipelines, ensure data quality, support ML workflows, and optimize query performance using various technologies.

The Data Engineer will design, build, and deploy scalable data solutions, optimize data flows, and implement ETL processes, leveraging various cloud platforms and technologies.

The Cloud Data Engineer will design and develop data warehouse solutions, create efficient data pipelines, collaborate with teams, and monitor system health.

As a Data Engineer, you'll build and support enterprise-scale data pipelines, ensuring data accuracy and quality while collaborating with various teams in an Agile environment.

The Data Engineer will develop and maintain AI context data capabilities, create data pipelines, ensure operational excellence, and follow compliance protocols. Responsibilities include data ingestion, retrieval quality improvements, and semantic layer implementation for AI integration within healthcare organizations.

The role involves building and maintaining AI data capabilities, implementing data pipelines, and ensuring operational excellence in data management within a healthcare context.

The Principal Data Engineer will design and implement data infrastructure for Voice AI products, lead a team of data engineers, and optimize data systems for machine learning. Responsibilities include building data pipelines, driving infrastructure strategy, and collaborating with cross-functional teams.

Design, build, and maintain ETL pipelines and big-data workflows from ingestion to consumption. Troubleshoot data/system issues, work in an agile team, handle structured/unstructured data and security logs, and support government data acquisition and sharing while meeting quality assurance and testing standards.

Design, implement, and maintain scalable, secure geospatial database solutions supporting ArcGIS web/desktop/mobile. Collaborate with cross-functional teams on requirements, configuration, backup/DR, performance tuning, security, automation of data workflows, and provide technical guidance throughout implementations for Defense and Intel clients.

Consult with customers to design and implement enterprise geospatial database solutions using Esri/ArcGIS technologies. Configure, secure, monitor, and automate databases (backup/HA/DR, performance tuning, data loading). Collaborate across teams, provide technical guidance, and support database migrations and integrations for mission-critical defense and intel applications.

Consult with customers to design and implement scalable, secure enterprise geospatial database solutions using Esri/ArcGIS technologies. Configure and maintain database environments (backup, HA/DR), monitor and tune performance, implement security and access controls, automate data workflows, and provide technical guidance across requirements, design, build, and deployment phases. Support integration with ArcGIS web, desktop, and mobile applications for Defense and Intel clients.

Design and implement scalable, secure enterprise geospatial database solutions using Esri technology. Collaborate across project phases to configure, maintain, tune, secure, and automate databases, support ArcGIS applications, and provide technical guidance for migrations, integrations, and operational readiness for Defense/Intel clients.

Design, implement, and maintain secure, high-availability geospatial and enterprise database solutions. Collaborate with cross-functional teams to configure, automate, monitor, and tune databases, enforce security and compliance, and provide technical guidance for migrations and integrations supporting ArcGIS web, desktop, and mobile workflows.

Build and maintain reproducible data pipelines to process, clean, transform, and integrate MIDUS survey data; manage metadata and documentation for public and non-public releases; maintain the MIDUS Colectica portal; collaborate with researchers and respond to data requests; select and optimize technologies for large-scale research data management.

The Senior Data Engineer will design and implement data architecture, manage production data pipelines, lead projects, and ensure quality and documentation while supporting progressive politics through data-driven solutions.

The Data Migration Engineer migrates customer data into SaaS products, ensuring data quality and business continuity while collaborating with teams and managing customer requirements.