Top Data & Analytics Jobs

Lead architecture and implementation of scalable data systems and pipelines from ingestion to delivery. Own ambiguous, high-impact integrations, improve data quality and reliability, adopt AI-augmented engineering, mentor engineers, and collaborate with Product, ML, and customer teams to ship production solutions.

The Data Analytics Engineer will build reliable data pipelines, transform data for analysis, and create dashboards and reports while collaborating with cross-functional teams.

Design, build, and lead a scalable, configuration-driven data integration platform. Improve performance, automate monitoring and deployments, provide escalated support, and collaborate across product and engineering to deliver reliable, secure data integrations.

As a Senior Data Engineer, you will build and optimize data pipelines, integrate AI capabilities, and collaborate across teams to create data-driven solutions, while providing technical leadership and ensuring data quality and governance.

As a Staff Data Engineer at DAT, you will partner with finance teams to build automated reporting systems, data models, and visualizations. You will ensure data accuracy and contribute to financial workflows and reporting processes with accountability and collaboration.

Design, optimize, and scale Snowflake-based data architecture and pipelines. Implement data observability, operationalize MLOps, build semantic enterprise models, and deploy AI-assisted agents and automation for production analytics and commercial data products. Share cross-functional ownership for pipeline resilience, monitoring, and model lifecycle management.

Design, build, and operate a privacy-safe, cloud-based data platform supporting batch and real-time pipelines, analytics, ML/AI, governance, observability, and high pipeline reliability. Partner with stakeholders, set data engineering standards, troubleshoot production incidents, and mentor engineers.

The Senior Data Engineer will develop and optimize software applications and data platforms for NAVOCEANO, supporting mission-critical solutions, data pipelines, and analytics capabilities.

Lead data engineering work across migrations, pipelines, integrations, and APIs. Design, build, deploy, test, monitor, and support production data solutions while ensuring data quality, validation, and adherence to architectural standards in an agile continuous-delivery environment.

Design, build, and operate production-grade data ingestion pipelines and dbt transformations into a Databricks lakehouse. Establish data quality, monitoring, and observability. Partner with Product and Engineering to enable metrics, dashboards, and longitudinal patient analytics supporting clinical and operational decision-making.

Lead design and implement scalable data infrastructure and transformations. Build data repositories, convert data science algorithms into robust pipelines, mentor a small data engineering team, ensure delivery quality, and collaborate with Product, Data Analysts, and Data Scientists.

The Senior Data Engineer will design and build scalable data solutions, manage data infrastructure and pipelines, and collaborate with teams to ensure data quality and drive business outcomes.

Design and implement scalable data infrastructure and production data transformations. Lead and mentor a small Data Engineering team, ensure quality delivery, collaborate with Product, Data Analysts, and Data Scientists to operationalize algorithms and build robust data repositories.

Lead modernization efforts for data infrastructure as a Senior Data Engineer, focusing on ETL pipeline development and Snowflake implementation while mentoring peers and ensuring data security.

The Staff Data Engineer will enhance the data ecosystem at WeightWatchers by developing data pipelines, collaborating cross-functionally, and ensuring data quality while leading projects and technical initiatives.

Lead data architecture and hands-on engineering to build a cloud data warehouse on Snowflake using Data Vault 2.0 and dbt. Design standards, implement ETL/ELT pipelines with Python and SQL, ensure data quality and governance, mentor engineers, and support on-prem to cloud migration.

The Senior Data Engineer Lead will design, build, and oversee data architecture, mentor engineers, and drive data strategy and culture at Citi.

The role requires designing, building, and maintaining data pipelines using Big Data technologies. Responsibilities include developing ETL processes, ensuring data integrity, collaborating with teams, and applying AI techniques to drive efficiency.

The Data Engineer will design and maintain data pipelines using Big Data technologies, optimize ETL processes, and apply AI techniques. Responsibilities include collaborating on data solutions and ensuring data quality and security.

The Senior Data Engineer is responsible for building AI-driven healthcare automation systems, managing data workflows, and ensuring accurate reporting, particularly in healthcare claims processes.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

Design, implement, and support enterprise data integrations connecting JDE, Workday, Salesforce and other platforms. Lead SQL-driven ETL/ELT pipelines, develop reusable integration frameworks, ensure data integrity and audit readiness, perform regression and production troubleshooting, and provide architectural oversight and mentorship across multiple concurrent projects.

Design, build, and maintain Snowflake-centered data warehouse and scalable ETL/ELT pipelines using IaC and orchestration tools; optimize performance, ensure data quality/security, support analytics and ML, and collaborate with cross-functional teams.

Design, build and scale a 500+ TB Audience Management Big Data platform. Own data ingestion, validation, transformation and storage pipelines. Write server-side Spark/Scala code, perform R&D on new technologies, mentor engineers, and partner with product managers to meet roadmap and business needs.

As a Data Operations Engineer, you will manage partner data lifecycle, ensuring data quality and performance while collaborating with teams to enhance data integration processes and guide architecture decisions.