Top Data Engineer Jobs

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.

As a Lead Data Engineer, you'll design and implement full-stack technical solutions, collaborate across Agile teams, and leverage big data and cloud technologies to deliver personalized customer experiences.

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.

Lead Data Engineer role focused on building data solutions, collaborating across Agile teams, utilizing big data and cloud technologies, and mentoring team members.

The Senior Data Engineer will manage and optimize Oracle Databases, conduct data migrations, perform performance tuning, and provide operational support. They will also participate in system upgrades and on-call rotations.

The Data Engineer II will design and implement scalable data pipelines, collaborate with stakeholders, ensure data quality, and support analytics by utilizing cloud platforms and big data technologies.

The Data Engineer II will design, develop, and maintain data pipelines, ensure data accuracy, and optimize data processes while collaborating with various teams.

As a Data Engineer II, you will develop AI Data Agents in Snowflake, manage data integrations, and partner with teams to enhance business use cases.

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.

Build and maintain scalable batch and real-time data pipelines using Kafka, Google Dataflow, Snowflake and S3. Integrate APIs via Apigee, ensure data quality, publish data for reporting, and collaborate with stakeholders to document workflows and support analytics.

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.

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.

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.

The Data Engineer will develop data pipelines, advise clients on cloud solutions, and collaborate to maximize data architecture value.

CapTech seeks a Data Engineer to develop data pipelines, advise clients on cloud technologies, and collaborate on data architecture solutions while leveraging AWS, Azure, or GCP.

The Databricks Data Engineer will design and implement ETL pipelines, manage data ingestion processes, and collaborate with business teams to create analytics solutions.

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.

The Sr. Snowflake Data Engineer will design and optimize data pipelines, support mission-critical applications, and ensure data integrity and performance on cloud infrastructure.

The Data Engineer role involves designing and maintaining AWS-cloud-native data systems, developing ETL processes, optimizing data pipelines, and ensuring data security and governance in healthcare data applications.

The Sr. Databricks Data Engineer will design, develop, and optimize data pipelines using Databricks, while ensuring scalable solutions and addressing data issues. Responsibilities include collaborating with teams, conducting impact analysis, and maintaining software lifecycle processes.