Top Data & Analytics Jobs

The Integration Engineer designs and implements data integration solutions, ensuring data quality and governance across diverse domains while building scalable streaming and batch data pipelines.

Lead the design and optimization of data pipelines, mentor junior engineers, establish data standards, and collaborate on data solutions.

Design, build, and maintain scalable data pipelines and infrastructure on AWS, collaborating with data scientists and AI teams to support analytics and ML initiatives.

Lead the design and development of data pipelines, mentor junior engineers, and implement best practices for data systems optimization and governance.

Responsible for assessing and improving data quality. Collaborates with developers to implement data logic, conducts quality reviews, and communicates issues to resolve data quality problems. Provides support to ETL teams and manages customer requirements throughout the project lifecycle.

The Senior Data Engineer is responsible for building and maintaining data pipelines, defining metrics, and collaborating with cross-functional teams to ensure data quality, governance, and operational excellence.

The Data Ingestion Specialist will manage the ingestion of healthcare data, improve data models, debug issues, and collaborate with team members to maintain pipeline reliability and efficiency.

Design, build, and operate scalable data architectures and ETL/ELT pipelines across cloud and on-prem systems; enable ML/analytics, ensure data quality and compliance, mentor junior engineers, and support 24/7 reliability.

The Senior Data Engineer will enhance data lakes, develop efficient data pipelines, and collaborate with cross-functional teams to solve complex business problems using various technologies.

Lead design and delivery of data platform and analytics solutions, maintain data lake and catalogs, mentor ACE team, drive ROI-focused analytics projects, and enable data-driven decision-making across the business.

As a Lead Data Engineer, you'll optimize data workflows, manage data engineering projects, mentor junior engineers, and ensure robust data solutions meet business needs.

Lead design, build, and maintenance of scalable data pipelines and lakehouse infrastructure using PySpark, Databricks, and Airflow. Own data & ML platform (Terraform, Databricks), improve observability, data quality, and developer tooling, and partner closely with Data Science and engineering teams.

Lead and mentor technical resolution of complex Data & AI production issues for customers, deep-dive into data pipelines and AI workflows, troubleshoot Spark/Delta/DLT/Model Serving, influence product improvements, and guide architects to build performant, reliable Databricks-based solutions.

Operate and automate LendingTree's cloud data platform (Snowflake) by building CI/CD, troubleshooting ETL/streaming (Kafka), integrating with AWS/Azure services, enforcing security and observability, and partnering with data engineering to improve reliability and cost-efficiency.

The Senior Data Engineer will build and maintain ELT pipelines, manage data workflows, and improve the data warehouse quality while ensuring data integrity and accessibility for stakeholders.

Seeking a Senior Data Engineer to develop scalable data solutions and pipelines on Databricks and AWS, ensuring data quality and promoting engineering excellence.

The Data Integration Engineer will design, build, and maintain data pipelines and integrations across AWS and Snowflake, ensuring data quality and security while optimizing performance. They will collaborate with various technical teams to implement scalable solutions and document processes for maintainability.

As a Senior Data Engineer, you will design and maintain data infrastructure, implement ETL processes, and optimize data workflows using Python and PySpark.

As a Staff Data Engineer, you will design and build data solutions, lead projects, mentor team members, and ensure services are secure and scalable.

Design and maintain data pipelines and infrastructure, ensuring data quality and enabling analytics and machine learning. Collaborate with teams to optimize data workflows and architecture.

Design and build data pipelines and infrastructure; maintain data quality and accessibility; optimize data warehouse architecture while collaborating with teams to meet data needs.

The Senior Data Engineer will design and optimize data pipelines and ingestion strategies to support analytics and AI across Watts. Responsibilities include implementing data engineering best practices and mentoring junior engineers.

Design and build scalable platforms for data ingestion and storage, collaborate with hardware engineers, and define engineering processes at Sift.

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.

The Senior Data Engineer will design and maintain data infrastructure and pipelines, ensuring data integrity and supporting analytics for a nonprofit organization.