Top Data & Analytics Jobs

Design, configure, and operate data governance tooling for unstructured and structured data. Implement metadata cataloging, lineage harvesting, automated data quality checks, and governance workflows. Build prototypes, dashboards, and connectors using Python, SQL, Databricks, and Streamlit. Collaborate with stakeholders to define critical data elements, prioritize remediation, produce documentation, and drive tool adoption via trainings and enablement.

Build and maintain ETL/ELT pipelines, ingest and transform structured and unstructured data, integrate APIs and external sources, improve data quality and monitoring, support dashboards and ML pipelines, optimize warehouse and cloud performance, and contribute to data governance and documentation.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Design and maintain scalable batch and real-time data pipelines, build governed data models for a CDP, ensure data quality and security, support identity resolution and customer 360, mentor junior engineers, and collaborate with analytics and business stakeholders to deliver actionable customer insights.

As an Azure Data Platform Consultant, you will deliver data solutions using Azure and Fabric, engage with clients, design solutions, and optimize data platforms.

The Data Engineer will lead data lifecycle strategy, manage data acquisition and cleansing, and collaborate with teams to optimize data solutions and architecture.

The Data Engineer will build and optimize data pipelines and cloud solutions, collaborating with teams to ensure data quality and leveraging modern engineering tools.

The role involves building and maintaining data pipelines, ensuring data quality, and collaborating with clinical researchers to provide clean datasets for analysis.

As a Data Engineer, you'll deliver scalable data solutions, participate in technical discussions, and ensure timely, trustworthy data delivery through robust pipelines.

The Data Engineer will develop and implement software solutions for law enforcement, focusing on data management, system optimization, and effective communication with clients.

The Data Engineer will develop data and software solutions for law enforcement, create reports, and manage data sources. Responsibilities include collaborating with teams to analyze data, communicate with clients, and ensure high-performance analytics tools.

As a Data Engineer, you will build and optimize data pipelines, ensuring accurate data delivery that informs pricing and market analytics at Alt.

Responsible for building and operating scalable lakehouse data pipelines, optimizing data flows, and delivering analytics-ready data products using Azure Databricks technologies.

The Data Engineer will transform raw data into useful systems by building pipelines, conducting analysis, and collaborating on projects. Responsibilities include developing algorithms and enhancing data quality.

The role involves engineering modern data platforms, focusing on data ingestion, transformation, and storage while utilizing Azure services and MS Fabric, supporting an investment management firm.

The Senior Bioinformatics Data Engineer will build data pipelines, implement clinical data ingestion, and optimize platform infrastructure while ensuring data quality and compliance with legal standards.

Designs, builds, and maintains scalable ETL pipelines and databases; integrates large-scale data for analytics; develops and tests code, queries, and reports; ensures data quality and governance; leads solution development, trains users, and supports ML and BI initiatives.

Design and maintain executive Power BI dashboards and Power Apps, translate clinical and financial data into actionable insights, build frontend data products, educate end-users, partner with backend engineers to build pipelines in Microsoft Fabric, and perform ad-hoc healthcare analytics and modeling to support operational leaders.

Provide senior-level data engineering for analytics: resolve complex technical issues, build decision-support reports and dashboards, lead projects, prepare and integrate data, coach staff, and ensure high-quality analytics to support academic, research, and healthcare goals.

Design, build, and maintain scalable cloud data pipelines and Databricks-based data platforms. Manage Databricks clusters and Delta Lake tables, integrate with Azure services, implement CI/CD and monitoring, define data warehouse architecture and governance, collaborate with stakeholders, and support advanced analytics and future AI/ML use cases.

Design, build, and maintain data pipelines, ETL processes, and data warehousing solutions using Python and GCP/BigQuery. Ensure data quality, optimize storage and processing, support new data products, and mentor junior engineers while collaborating with the CTO and team.

Design, develop, and maintain scalable data pipelines, ETL processes, and BigQuery/GCP-based data storage. Ensure data quality, implement monitoring, assist product launches, mentor junior engineers, and collaborate closely with the CTO and team.

Design, build, operationalize, and maintain enterprise-scale data pipelines and platforms. Develop ETL/ELT workflows, parse structured and unstructured data, troubleshoot Palantir Foundry pipelines, and lead cross-functional teams to support analytics, monitoring, and scalable data solutions for mission-driven projects.

Design, implement, and maintain scalable data pipelines and storage for intelligence operations. Build ETL and real-time ingestion, optimize queries and data models, enforce data quality, governance, and security per IC standards, and collaborate with analysts and mission partners.

Lead Data Engineer responsible for building technical solutions, collaborating with Agile teams, utilizing big data technologies, and developing cloud-based data warehousing solutions to enhance user experiences.