Top Data Engineer Jobs

The Data Engineer will enhance data pipelines, support data analysts, and optimize data architecture for cross-functional teams. This role involves data extraction, transformation, and analytics to meet reporting needs.

The Data Engineer will manage data pipelines for financial institutions, translating raw transactions into insights while collaborating with various teams to enhance data models and tools.

The Data Engineer will clean, manage, and analyze datasets, automate ETL processes, and collaborate with traders and software engineers to derive insights.

The Data Engineer (AI) Senior Engineer will develop and maintain data pipelines, ensure data quality, implement deployment processes, provide training, and comply with military standards.

The Data Engineer will design and maintain scalable data pipelines, optimize ETL processes, and ensure data quality for analytics in healthcare.

Lead cross-functional Agile teams to design, build, test, and support cloud-based data solutions. Develop full-stack data engineering systems using Java/Scala/Python, RDBMS and NoSQL, Redshift/Snowflake, and distributed tools (Hadoop, Spark, Kafka). Mentor engineers, perform code reviews and unit testing, and collaborate with product managers to deliver scalable, performant data products.

Lead design, implementation, automation, and maintenance of large-scale ETL pipelines and scalable data solutions. Translate business questions into data requirements, validate and test datasets, mentor junior engineers, collaborate with analytics and stakeholders, and ensure robust, production-ready data solutions across global clients.

As a Senior Data Engineer, you will design and maintain data pipelines, define governance standards, and collaborate across teams to enhance Headway’s data architecture.

Seeking a Senior Data Engineer to design and optimize data pipelines, develop backend services, and implement Snowflake models, ensuring efficient data delivery in complex environments.

The role involves migrating on-premises databases to AWS, developing Python scripts for data processing, and building AWS data pipelines. Responsibilities include supporting application teams, data modeling, and ensuring system efficiency.

As a Data Engineer at LiveKit, you will manage the analytics infrastructure, develop scalable GCP-based data pipelines, and ensure effective data movement and transformation processes, while collaborating with the Analytics and engineering teams.

Build and maintain scalable ETL/ELT pipelines and data warehouse infrastructure, monitor performance and data integrity, troubleshoot issues, collaborate with teams to deliver reliable data solutions, and document processes.

Build and maintain ETL/ELT data pipelines, prepare and profile analytical datasets, perform database feature engineering, support anomaly detection, collaborate with data scientists and product owners, and define data quality practices to deliver reliable data products.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.

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 Senior will optimize data pipelines, work within scrum teams, mentor others, and improve data quality, reliability, and governance.

The Data Engineer will design, build, and maintain scalable data pipelines, collaborating with cross-functional teams to support analytics and business operations.

The Data Engineer will design and optimize ETL jobs using PySpark, build data pipelines, and collaborate on enterprise data systems.

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.

The Data Engineer will develop cloud-based data pipelines, collaborate with clients on data architecture, and utilize engineering best practices to provide effective data solutions.

The Data Engineer will develop data pipelines and solutions on cloud platforms, advise clients, collaborate with users, and ensure effective data architecture.

Data Engineers at CapTech develop data pipelines using AWS, Azure, or GCP, advising clients on optimal cloud solutions and enhancing data architecture.

The Data Engineer will develop data pipelines, collaborate with clients, advise on cloud technologies, and solve complex data problems.

Data Engineers at CapTech build and maintain data pipelines on cloud platforms, advise clients on technology usage, and ensure data architecture maximizes client value.

Data Engineer to develop data pipelines using AWS, Azure, or GCP, advise clients on cloud resources, and collaborate with stakeholders to enhance data architecture.