Top Data Engineer Jobs

Design, build, and maintain scalable Azure-based data pipelines, lakes, and warehouses. Create ETL/ELT processes, dimensional models, and business-ready datasets. Support reporting and Power BI, implement data quality, governance, monitoring, and document platform architecture and processes while partnering with stakeholders.

As a Senior Data Engineer, you will build and maintain data pipelines, enhance analytics capabilities, manage data integration, and guide team members in transforming complex data into actionable insights.

The Data Solutions Engineer will design and deliver data and analytics solutions, manage data pipelines, and support cloud platforms while collaborating with various teams to improve data accessibility and operational efficiency.

The Sr. ETL Informatica Systems Engineer develops ETL applications for the EDW/BI program using Informatica tools, managing complex SQL and APIs.

As a Lead Data Engineer, you'll design scalable data frameworks, develop data pipelines, implement data quality checks, and collaborate with stakeholders to enhance data solutions.

Lead the development and optimization of data transformation processes using dbt Core, Snowflake, and Python. Mentor engineers and ensure deliverables meet analytics needs.

The Senior Data Engineer will design and operate data systems, optimize data pipelines, and enhance AI workflows for legal operations. Responsibilities include data modeling, implementing governance standards, collaborating with cross-functional teams, and mentoring junior engineers.

The Senior/Staff Data Engineer will design and scale the core data platform for healthcare systems, focusing on infrastructure, tooling, and governance while mentoring engineers and collaborating with various teams.

The Senior Data Engineer will design and build scalable data platforms, handle automation for data operations, and ensure reliability and performance of data pipelines while collaborating with various teams.

Own and harden Plot's core data platform: stabilize high-throughput ingestion, design read-optimized schemas and partitioning, separate transactional vs analytical workloads, ensure performant data access for dashboards and AI agents, write RFCs, and raise reliability and observability across teams.

Design and modernize a scalable, secure data platform: build ETL/ELT pipelines (batch and near-real-time), migrate/operate SQL Server on AWS RDS, support transition to Microsoft Fabric, optimize performance, enforce security and governance (SOC 2), and enable AI-ready data in collaboration with engineering and business teams.

Design, build, and maintain scalable data models, ETL/streaming pipelines, and cloud-native data platforms. Ensure data quality, governance, performance tuning, and enable ML workflows. Lead cross-functional teams, mentor engineers, and implement CI/CD, monitoring, and cost-optimized solutions to support analytics and real-time inference.

Senior Data Developer designing, developing, testing and deploying cloud-native data solutions on AWS. Build automation, integrations, data models and analytics, participate in architecture and code reviews, mentor peers, and collaborate with analytics and ML teams to enable business-driven analytics.

Design, build, and optimize scalable ETL/ELT pipelines and cloud data platforms. Integrate data from SQL Server, Yardi, Salesforce and APIs into AWS (S3, Redshift). Collaborate with analytics, data science, and business teams to deliver trusted datasets, ensure data quality and governance, and implement DevOps, CI/CD, and infrastructure automation for operational excellence.

Build, operate, and modernize scalable data pipelines and warehouse environments for lottery reporting, analytics, and AI readiness. Improve ingestion, transformations, data models, contracts, observability, lineage, and onboarding patterns. Automate operations, troubleshoot production issues, mentor engineers, and support migration from legacy to cloud architectures while ensuring data quality, reliability, and regulatory continuity.

Design, build, and maintain cloud-native data infrastructure and pipelines (AWS, Terraform, Spark/PySpark). Partner with analytics consumers to model data, ensure data quality across healthcare domains, manage BI lifecycle, enable self-service, and collaborate cross-functionally to deliver scalable ETL and warehousing solutions.

Lead design, operation, and reliability of production data pipelines in a multi-terabyte Snowflake environment. Translate client requirements into dimensional models, debug and remediate pipeline failures, evolve the data mart for event-driven and AI workflows, and improve pipeline trustworthiness via testing, CI/CD, audit logging, and documentation.

Design, build and maintain a self-service data platform to enable teams to create data products. Support real-time analytics, batch processing and ML workloads. Implement secure, scalable, compliant infrastructure with IaC and automation. Enable ingestion, processing and consumption of data at scale. Mentor teammates and drive engineering excellence.

Design and develop scalable analytics software and prototypes using AWS and big-data technologies. Consult with stakeholders to define complex requirements, coordinate cross-functional teams, ensure disaster recovery, assign and direct staff, evaluate solutions, and prepare progress reports.

Support and evolve the enterprise analytics platform: build and maintain cloud data pipelines (ingest, transform, curate), develop analytics-ready datasets, create Power BI reports and semantic models, apply Python and AI workflows for automation and validation, ensure data quality and governance, and partner with finance and IT to deliver trusted analytics.

As a Senior Data & Integrations Engineer, you will design and govern data architecture, manage integrations, and ensure data reliability and scalability while collaborating with various teams.

As a Senior Data Engineer at Auger, you will build data systems to transform customer data into a unified ontology for analytics and AI workflows, ensuring data quality and managing the data lifecycle.

The Technology Analyst will develop Big Data applications leveraging Hadoop, Java, and Python. Responsibilities include project lifecycle participation, team collaboration, and client interfacing in a global delivery environment.

The role involves building scalable ELT/ETL pipelines on GCP, utilizing SQL and Python, and managing security and infrastructure automation while ensuring real-time processing and resource provisioning.

The Solution Engineer - Data Engineering Specialist will provide technical leadership in the financial services sector, collaborating with sales teams to demonstrate Snowflake's data platform capabilities while engaging with technical and executive stakeholders.