Top Data & Analytics Jobs

The Lead Data Engineer will architect and optimize data pipelines, leading a team to create scalable data solutions that support analytics and decision-making.

The Data Engineer, Senior will design and maintain data systems, build ETL pipelines, and collaborate with a team to optimize data solutions for client missions.

The Data Engineer will design and build scalable data pipelines, optimize data infrastructure, and collaborate with teams for data solutions in an eCommerce environment.

As a Data Engineer, you'll build data solutions, support analytics, and ensure data quality while collaborating across teams to optimize data management.

As an ETL Data Engineer, you'll design and maintain data integration processes using Python and Azure Synapse Analytics, ensuring data accuracy for insights. You'll collaborate with teams, implement data quality checks, and contribute to performance tuning and data modeling.

The Azure Data Engineer will design and develop ETL processes, utilizing Python and Azure Synapse Analytics, to manage data integration and ensure data accuracy. Responsibilities include performance tuning, data modeling, and collaboration across teams.

Lead design, development, and maintenance of Azure data pipelines and solutions (ADF, Azure SQL). Implement CI/CD, perform data modeling, ensure data quality and scalability, support deployments and production operations, and collaborate with architects, analysts, and business stakeholders to deliver governed, reliable analytics-ready data.

As a Senior Lead Data Engineer, you'll lead development teams, design technical solutions, utilize big data and cloud technologies, and drive transformation initiatives.

Lead the design and implementation of technical solutions using big data technologies. Collaborate with teams to deliver cloud-based data solutions and support Agile practices.

Design and build foundational dimensional data models, enterprise metrics, and curated data products on a modern lakehouse. Partner with business domains to translate processes into scalable, high-quality datasets, optimize analytical workloads, and operate distributed processing systems to support analytics, BI, and AI.

The Founding Data Engineer will manage the company's data models, ensure metric integrity, and work with various teams to deliver reliable metrics and reporting systems.

As a Data Engineer, you will design and implement data solutions, automate processes, and support data analytics for the Department of Defense.

The Data Engineer will develop scalable data pipelines, build applications using Palantir Foundry, and collaborate with stakeholders on data integration for decision-making.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts; integrate data for analytics and Data Science; optimize Hadoop/HDFS and queries; implement CI/CD and cloud-based big-data solutions; collaborate with Data Science to operationalize models and troubleshoot systems.

Design, build, and maintain large-scale data structures, ETL pipelines, and data models to support analytics and reporting. Integrate data from varied sources, collaborate with Data Science to operationalize models, optimize Hadoop/Spark workflows, and ensure data quality and accessibility for internal customers.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts. Integrate data from multiple sources, ensure data quality, optimize Hadoop/HDFS workflows, collaborate with Data Science to operationalize models, and recommend tooling and system improvements.

Design, build, and manage large-scale data structures, pipelines and ETL workflows. Develop real-time and batch analytic systems, integrate diverse data sources, ensure data quality and accessibility, and collaborate with Data Science to operationalize models using Hadoop, GCP, Python, Spark, Airflow, and related tools.

Design, build and maintain large-scale data structures, ETL pipelines, and data marts. Integrate data sources, ensure data quality, support analytics and Data Science teams, and optimize Hadoop/cloud-based processing using tools like Spark, Airflow, and Kafka.

Build and maintain large-scale data structures, pipelines, and ETL workflows; design data architectures and models; integrate data for analytics and data science; collaborate with Data Science to productionize models; ensure data quality, accessibility, and compliance for healthcare and retail use cases.

Build and maintain large-scale data structures, pipelines, and ETL workflows; design databases and data marts; collaborate with Data Science to integrate models; ensure data quality and accessibility; leverage Hadoop, Spark, Python/Java, and cloud platforms to deploy scalable ML-enabled data solutions.

Develop and support contractual data reporting and post-production reporting for manufacturers. Review and redline data reporting contracts, assess feasibility, perform root cause analysis, write and run SQL queries, manage ETL processes, design data models, and maintain project documentation while collaborating with internal teams and partners.

Design, build, and maintain large-scale data structures, ETL pipelines, and data architectures to support analytics and reporting. Integrate data sources, ensure data quality and accessibility, collaborate with Data Science to operationalize models, and troubleshoot/optimize systems using Hadoop, cloud platforms, and modern data tooling.

Design, build, and maintain large-scale data structures, ETL pipelines, and data models on cloud platforms (GCP/BigQuery, AWS, Azure). Collaborate with Data Science to integrate models, ensure data quality, troubleshoot systems, and support analytics modernization.

Build and manage large-scale data structures, ETL pipelines, and data marts; design database systems and distributed computing architectures; integrate data for analytics and productionize ML/NLP models; collaborate with Data Science, ensure data quality, optimize queries, and troubleshoot systems.

Design, build, and maintain cloud-native data platforms and large-scale ETL pipelines. Integrate data for analytics and data science, support CI/CD and production operations, advise on tooling, ensure data quality and privacy, and mentor junior cloud engineers to support healthcare data modernization.