Top Data & Analytics Jobs

Builds and optimizes ETL/ELT pipelines, integrates disparate data sources, ensures data quality/security, supports analysts and data scientists, and implements data governance and metadata management.

Support DaaS/Digital Marketplace deployments and data set publishing across Google Marketplace, AWS, and Snowflake. Automate uploads/refreshes, QC steps, and product configurations; troubleshoot integrations; create buckets/views/shares; develop repeatable automation frameworks; collaborate in an Agile team and manage multiple tasks independently to ensure timely, accurate delivery of data pipelines and product data sets.

Design, build, and maintain Databricks-based ETL/ELT pipelines and medallion (bronze/silver/gold) lakehouse architectures. Ensure data quality, lineage, governance, and performance for large federal health datasets. Collaborate with data scientists, analysts, and CMS stakeholders and support Agile development and CI/CD workflows.

As a Lead Data Engineer, you will design and develop solutions, collaborate with teams on data technologies, and support cloud-based data warehousing and big data applications.

The Lead Data Engineer will design and develop technical solutions, collaborate with agile teams, and implement cloud-based data solutions, focusing on real-time data applications and big data technologies.

Design and maintain scalable cloud analytics data models and semantic layers, integrate ERP/project/operational systems, preserve business context, define modeling standards, deliver dashboards and reports, partner with stakeholders on metrics, and support planning and forecasting to enable enterprise reporting and decision-making.

Designs and builds scalable distributed data processing systems and data warehouse solutions on-prem and in AWS. Develops ETL/ELT pipelines, optimizes databases, implements CI/CD, mentors team members, liaises with business units, and ensures performance, reliability, security, and documentation for BI and analytics applications.

Lead design, implementation, automation, and maintenance of large-scale ETL pipelines and scalable data solutions. Optimize SQL and database performance, collaborate with analytics and business stakeholders to translate needs into data requirements, apply best practices (version control, code reviews, data validation), mentor junior engineers, and ensure delivery of accurate, robust data products while complying with internal policies and regulations.

Design, build, and maintain end-to-end data pipelines and integrations using Azure Data Factory, DBT, and Snowflake. Optimize SQL and Snowflake performance, support batch ingestion and API-based integrations, mentor engineers, produce technical documentation and runbooks, and ensure data quality, monitoring, and secure compliant data transfers.

Design, develop, and deploy AI-powered data solutions, optimize ETL processes, build data pipelines, and create executive dashboards, while collaborating with product leaders.

Build and own customer data ingestion and large-scale pipelines powering AI workers. Design syncing, retrieval, and data lake systems, improve reliability/observability, partner with product/backend teams, and contribute across infrastructure to give AI agents access to enriched customer data.

The Data Engineer designs and maintains scalable data products, implements quality checks, and supports analytics and reporting needs, collaborating closely with business stakeholders to ensure data reliability.

The Data Engineer II will design, build, and deploy data solutions that enable organization-wide access to data, supporting AI, Machine Learning, and business intelligence. Responsibilities include creating data pipelines, ensuring data quality, and collaborating with teams to enhance data products.

As a Data Engineer at Calico, you'll develop infrastructure for research data, collaborate on projects, mentor junior engineers, and ensure data governance.

The Principal Data Engineer will lead development projects, design scalable data pipelines, ensure data quality, and mentor a team of engineers while collaborating with stakeholders.

Lead and mentor a data engineering team, define technical vision and strategy, oversee data pipeline design, and collaborate with cross-functional teams.

Support design, development, and maintenance of scalable ETL/ELT data pipelines and modern data platforms using Azure and Microsoft Fabric. Build and optimize data models, write SQL for transformations and validation, monitor workflows, troubleshoot issues, and collaborate with analysts and stakeholders. Contribute to data governance, documentation, automation, and continuous improvement.

Design, build, and maintain scalable data assets and pipelines for analytics and ML; validate and ingest diverse data sources; perform exploratory data analysis and data quality checks; collaborate with cross-functional teams and produce reproducible code and documentation.

Build, validate, and operate enterprise data connector integrations and ETL pipelines (T1-T3). Maintain data quality frameworks, handle schema/API changes, produce mapping documentation, support MCP endpoint integrations for AI agents, and own production pipeline reliability and onboarding of incoming engineers throughout the engagement.

The Palantir Data Engineer will design and maintain ontologies, implement data pipelines, and ensure data integrity while collaborating with product owners and teams.

Design, build, and maintain scalable data pipelines and ETL processes in Azure (Synapse, Data Factory). Integrate data via APIs, ensure data quality/security, support analytics and Power BI reporting, collaborate with stakeholders, and manage work using Agile/Jira to support federal healthcare and VA initiatives.

Build, maintain, and support scalable data systems and pipelines. Ingest, clean, structure, and enrich data from multiple sources. Ensure data quality, security, and governance. Collaborate with analysts and data scientists to design solutions, deploy and optimize pipelines, and diagnose and resolve data issues to support analytics and reporting.

Design and maintain pipelines and tooling to ingest, validate, model, and serve multi-modal driving data for ML training, evaluation, and debugging. Collaborate with ML, vehicle software, curation, and fleet teams to scale the data stack and make datasets discoverable and queryable.

As a Senior Lead Data Engineer, you'll lead a development team, design and implement data solutions using machine learning, distributed systems, and full-stack technologies, while collaborating with Agile teams and ensuring code quality.

Lead design and deliver cloud-based data engineering solutions across Agile teams. Build, test, and support full-stack data systems using big data, streaming, and cloud technologies; mentor engineers and ensure high-performance, well-tested code.