Top Data Engineer Jobs

The Senior Data Engineer will design and maintain data processing systems, enhance ETL components, and ensure data security and integrity while mentoring junior staff.

As a Data Solutions Engineer, you'll manage customer data migrations and GIS onboarding from legacy systems, ensuring data quality and accuracy while interfacing with government staff.

The Senior Data Engineer will develop scalable services, design data integration solutions, manage data pipelines, and ensure compliance in applications as part of a collaborative team.

The Senior Data Engineer will design and maintain scalable ETL/ELT pipelines, develop data models, ensure data quality, and collaborate with cross-functional teams to drive analytics and machine learning operations.

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.

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/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, 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.

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 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.

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 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.

Design, build, and maintain enterprise data engineering solutions and ETL/ELT pipelines using ADF, SSIS, and SAP Data Services. Develop and optimize database schemas and complex SQL in Oracle and SQL Server, implement data warehouse/data lake architectures (star/snowflake), ensure data quality and governance, create Power BI reports, automate workflows with Python and Shell, troubleshoot pipeline failures, support SDLC, and mentor junior engineers.

Lead architecture and scaling of the Databricks data warehouse and self-service data platform. Build reusable batch and streaming frameworks, enforce governance, SLOs, lineage, observability, CI/CD, and multi-tenancy. Mentor engineers, run design reviews, and ship documented patterns to enable analytics, data science, and app teams to move quickly without blocking on platform tickets.

The Senior Data Engineer designs and develops scalable data architectures across platforms, mentors team members, and enhances data engineering capabilities for insights and decision-making.

Lead architecture and modernization of the enterprise data platform. Build scalable serverless data pipelines with Airflow, dbt, Python, and AWS. Integrate Fivetran, Redshift, and Sigma, implement observability, enforce data governance, and mentor engineers to improve reliability and analytics deliverables.

Design, build, and maintain backend systems and data interactions for healthcare reporting. Develop APIs, data models, ETL pipelines, and interfaces; optimize performance, ensure data integrity and security, and support automated testing and CI/CD. Collaborate in Agile teams and reduce technical debt while enabling integrations with frontend and third-party systems.