Top Data Engineer Jobs

This co-op position involves developing data products, design and testing of data pipelines, and delivering insights from complex datasets for business decisions.

This co-op position involves developing data products and solving complex data problems using cloud technologies, SQL, and programming languages while gaining mentorship and business exposure.

As a Data Engineer, you will build and own the data infrastructure, design pipelines, ensure data quality, and implement DataOps practices while collaborating closely with product and engineering teams.

The Data Engineer will build and optimize data pipelines and infrastructure, ensuring data quality for analytics and machine learning initiatives while collaborating with teams to develop data solutions.

The Senior Data Engineer will build and maintain data pipelines, optimize data processes, design a data validation framework, and ensure user privacy and security.

Responsible for building ETL/ELT pipelines, optimizing data workflows, monitoring data quality, and collaborating with other teams for data governance and analytics.

The Principal Data Engineer will lead the Data Resolution team, focusing on complex data challenges using Spark, system architecture, and mentorship, to optimize graph data pipelines.

The Senior Data Engineer will design, build, and maintain scalable party data solutions, integrating cloud-native platforms and improving legacy systems while mentoring junior engineers.

Design, build, and operationalize data and ML pipelines on Databricks. Implement CI/CD and infrastructure-as-code, ensure data quality/governance, troubleshoot incidents, and collaborate cross-functionally to enable reproducible ML lifecycle and deployments.

As a Data Engineer, you will build and maintain scalable data pipelines, implement data engineering frameworks, and support AI initiatives. You will also design processes for data cleansing, transformation, and orchestration while adhering to engineering standards.

Lead and mentor multiple Databricks-focused data engineering teams, define engineering best practices and reusable frameworks, drive CI/CD and performance/cost optimization, build and support analytical and streaming pipelines, and collaborate with architects, product owners, and cross-functional partners to deliver high-quality data products.

As a Quantitative Developer, you'll innovate and enhance quantitative methods, develop custom tools, maintain data pipelines, and collaborate with researchers for advancing investment strategies.

As a Data Migration Engineer, you'll convert client banking data to the Q2 platform, troubleshoot issues, and manage multiple migration projects.

The Data Engineer will perform ETL/ELT operations, develop data solutions, maintain data structures in a data warehouse, and resolve data issues while collaborating with teams on projects.

The Data Engineer will execute data architecture projects, manage data ingestion processes, ensure data quality, and transition data to new systems while collaborating with investment teams.

As a Data Engineer, you will develop data pipelines and optimize data processing systems, collaborate with teams to fulfill data needs, and ensure data security. You'll work with large datasets using AWS services, implementing data architectures and providing mentorship.

Develop and optimize data pipelines for reporting and advanced analytics. Ensure data quality and create real-time processing applications. Collaborate with DevSecOps teams and enhance data management procedures.

The Data Engineer will design and optimize ETL pipelines, integrate data, ensure data quality, and troubleshoot issues, enabling decision-making across the organization.

Design, develop, and manage ETL workflows using Informatica PowerCenter; ensure data quality and reliable data flows; translate business needs into functional designs; write and optimize T-SQL/SQL, stored procedures and triggers; perform testing and manage production deployments with business teams.

Designs and implements scalable multi-tenant data solutions and pipelines using Python, SQL, Snowflake, Snaplogic, Azure and AWS. Leads architecture design, ensures QA readiness, documents systems, mentors engineers, and coordinates cross-team project delivery on-time and on-budget.

Design, build, and maintain scalable data platforms and pipelines (ETL/ELT). Support data ingestion, parsing, transformation, and analytics; collaborate with cross-functional teams to deploy and operate data solutions for mission-driven clients.

As a Data Engineer II (Tech Lead), you will design and build complex data solutions, optimize data transformation processes, and collaborate with teams to enhance analytical capabilities across the organization.

As a Data Engineer, you will design and implement data pipelines, analyze requirements, and develop software solutions to drive operational efficiency.

Lead the architecture and design of data and analytics solutions, focusing on ETL, data warehousing, and cloud technologies while collaborating with global teams to optimize data processes.

The Data Engineer will design and maintain scalable data pipelines and SQL database solutions, ensuring data quality and documentation across projects.