Top Data & Analytics Jobs

As a Palantir Data Engineer, you'll work on data exploration and analytics projects, apply innovative methodologies, and support military missions using AI solutions.

Design, build, and optimize scalable AWS-based data pipelines, data lakes, and warehouses. Migrate legacy systems, enforce data quality/security/governance, implement ETL/ELT and big-data solutions, adopt CI/CD and IaC, collaborate with stakeholders, and provide technical leadership and troubleshooting.

Design, build, and maintain scalable ELT pipelines and data models for insurance (Guidewire) domains and Generative AI. Ensure data quality, performance, governance, and security; support analytics, AI model training (embeddings, vector DBs), dashboards, testing, and mentoring.

Design, develop, and maintain ETL pipelines, databases, and data visualizations to support 300mm semiconductor manufacturing. Analyze operational performance, automate data extraction, troubleshoot systems, collaborate with stakeholders, and integrate emerging technologies to improve manufacturing efficiency.

Design, build, and maintain the company data warehouse and ETL processes. Partner with business teams to define data solutions and visualizations, support reporting (SSRS, Crystal Reports) and BI (Power BI/Tableau), troubleshoot issues, and provide occasional after-hours support.

Build and maintain ingestion pipelines, Python services, and dbt models on AWS and Snowflake. Own operational on-call responsibilities, migrate pipelines to Airflow, contribute to CI/CD, collaborate with BI/Analytics, and mentor junior teammates.

Design, build, and maintain scalable data pipelines, lakes, and infrastructure using Databricks, Spark, Python, and AWS. Collaborate with ML engineers, data scientists, and analysts to deliver data products, ensure data quality and governance, implement DevOps/SDLC practices, mentor junior engineers, and evaluate new data technologies.

Builds and operates CBP data pipelines: configures Airflow/Glue/Spark/Kafka flows, performs ETL/schema mapping, runs quality checks, applies security/IAM patterns, triages ingestion failures, updates documentation, and tracks data pipeline performance to support analytics and mission partners.

Design, build, modernize, and maintain operational and analytical data capabilities for Wealthscape Reporting, Analytics and Insights. Perform solution design, data analysis, ETL development, and production rollouts using Snowflake, AWS, cloud databases, and CI/CD pipelines. Collaborate across teams in a fast-paced financial services environment.

Design, build, and maintain operational and analytical data platform capabilities using Java Spring Batch, Python, AWS, Oracle, and Snowflake. Deliver end-to-end development, production rollout, and support; improve financial product data quality, modeling, and SQL performance; collaborate with business partners and squads.

Build and maintain production data pipelines and model implementations for Property and General Liability pricing. Collaborate with Actuarial and Data Science to translate requirements into scalable, cloud-native solutions, embed MLOps practices, establish data quality controls, provide technical leadership, and support modernization and monitoring for pricing models.

Design, build, and optimize data pipelines for massive datasets. Collaborate with stakeholders, implement CI/CD processes, and ensure data architecture scalability.

Design, build, and maintain scalable batch and real-time data pipelines and platform components. Produce curated datasets, ensure data quality, observability, and lineage, and collaborate cross-functionally to deliver data products that support analytics, experimentation, and ML.

The Data Engineer II will manage analytics pipelines for mobile games, transforming telemetry data and ensuring data quality for studio teams' decisions.

Build and maintain data pipelines and transformation layer using dbt and SQL; monitor replication and orchestration pipelines, add data quality checks, and develop datasets and dashboards for internal and client analytics. Collaborate with senior engineers, participate in code reviews, and gradually take on more ownership.

As a Data Engineer, you will develop data-driven decision analysis products for the DoD, ensuring effective stakeholder engagement, and leveraging advanced analytics and machine learning techniques.

The Data Engineer will develop data-driven decision analysis products, provide analytic consulting, support stakeholders with tools, and optimize defense systems for national security.

The Data Integration Lead designs and manages data ingestion pipelines, ensuring data integrity and security while supporting ETL processes in classified environments.

Designs, builds, deploys and supports enterprise data environments and pipelines across cloud and on-prem systems. Collaborates on infrastructure, monitoring, capacity planning, security, governance, disaster recovery, and integration with enterprise systems. Provides technical leadership for data management, testing, optimization, and operational support to meet SLAs.

Own and evolve Stream’s end-to-end revenue operations data platform. Build Python and dltHub ingestion pipelines, SQLMesh transformation models, dimensional data models, quality and observability systems, and GCP infrastructure centered on BigQuery. Integrate GTM systems, enable trusted analytics and reverse ETL, improve reliability and cost efficiency, and establish engineering standards. The role requires hands-on platform ownership in a fast-moving hybrid Boulder startup environment.

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.

As a Senior Data Engineer, you will automate processes, optimize data handling, build data products, and govern data while mentoring junior engineers.

Lead Data Engineer designs, builds, tests, and supports cloud-based data solutions. Collaborates with Agile teams on distributed, real-time, and full-stack systems using Java/Scala/Python, cloud data warehouses, big data and NoSQL technologies while mentoring peers.

Lead Data Engineer responsible for designing, developing, testing, implementing, and supporting cloud-based data solutions. Collaborate across Agile teams to build distributed, real-time data and streaming systems, mentor engineers, perform unit tests and code reviews, and leverage big data, NoSQL, and cloud data warehousing technologies.

Lead and mentor a data engineering team to design, build, test, and support cloud-based data solutions. Develop distributed, real-time and batch data pipelines using Java/Scala/Python, NoSQL and RDBMS, and cloud data warehousing (Redshift/Snowflake). Collaborate with product managers and Agile teams to deliver performant, production-ready systems.