Top Data Engineer Jobs

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 data infrastructure, client integrations, and data models to support analytics and AI at Trovo Health.

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.

Build scalable pipelines and infrastructure to collect, validate, curate, and publish large multimodal 3D/4D microscopy datasets; collaborate with labs and engineers, document provenance, apply statistical analysis and visualization, and support ML research and open-data access.

Build and maintain scalable data, model training, and inference pipelines for large multimodal 3D/4D microscopy datasets; implement multi-node GPU training/inference, ensure data provenance and quality, collaborate with scientists, document workflows, and support model deployment and public data release.

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.

Lead design and implement the core engine for an IoT platform: define metrics, implement an IoT query language and validator, build Spark and Flink execution paths, ensure parity between batch and stream, optimize Databricks/Delta Lake resources, and enforce data governance, quality, and security practices.

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.

Lead design and build real-time streaming pipelines for IoT using Apache Flink. Implement custom ProcessFunctions, state management, checkpointing, and data quality gates. Optimize Flink clusters on Azure, integrate shared libraries, and maintain CI/CD, monitoring, and documentation while promoting data governance and security.

The Data Analytics Engineer will enhance Salesforce analytics, translate business requirements into technical specifications, maintain data flows, and ensure data quality and reporting standards.

The Senior Data Product Engineer manages data products from inception to insight, collaborating with stakeholders and optimizing data pipelines with hands-on technical expertise.

Design, build, and maintain Azure-based data infrastructure and pipelines; integrate disparate data sources; implement data governance and quality; support retail analytics product discovery and insights; establish standards and best practices; mentor team members and consult cross-functionally to drive business growth.

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 will analyze data quality, design prediction algorithms, collaborate with the engineering team, and generate business insights.

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

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.

Responsible for designing, building, and maintaining data pipelines and infrastructure, collaborating with data scientists and stakeholders to support data-driven decisions.

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 posting contains company and benefits information but no role-specific responsibilities. The title indicates a Data Engineer supporting digital marketing, likely focusing on data pipelines, analytics, and collaboration with marketing and engineering 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 assist in testing and deploying applications, implementing data quality and warehouse pipelines, and collaborating with various teams.

The Data Engineer will design and manage data pipelines, develop datasets for product metrics, and collaborate with teams to ensure robust data integration and processing.