Top Data & Analytics Jobs

Build and maintain scalable production data pipelines, infrastructure, warehouse models, analytics platforms, and data-quality systems. Partner with software engineers to instrument product features and ensure reliable event data. Support Hex and Snowflake self-serve analytics, maintain business metrics and data logic, and develop monitoring, validation, alerting, and observability tooling. The role also collaborates with product, analytics, marketing, and engineering teams, with potential future exposure to recommendation and LLM-based product work.

Designs and maintains healthcare data pipelines, ETL workflows, databases, schemas, and analytical frameworks. Analyzes claims and related healthcare data to identify trends and insights, while ensuring data quality and integrity. Creates reports, dashboards, and visualizations for nontechnical stakeholders. Collaborates with healthcare policy experts, analysts, and stakeholders to translate requirements into data solutions and improve infrastructure, processes, and analytics capabilities.

Build, optimize, and maintain data pipelines, ETL processes, data architectures, AI solutions, and analytics platforms. Develop cloud-based solutions using Azure Functions and containerization, implement CI/CD workflows, integrate databases and APIs, and ensure data quality, monitoring, reliability, and documentation. Troubleshoot production issues, collaborate with cross-functional teams, and apply modern data engineering, AI, cloud, and DevOps practices.

Build and maintain batch and streaming data pipelines supporting enterprise analytics and AI. Develop transformations, analytical data models, quality checks, integrations, and reliable production workflows. Monitor and troubleshoot pipeline issues, support data-source onboarding, optimize platform performance and costs, and follow governance and security standards. Collaborate with BI developers, analysts, and data scientists while writing tested, documented code in an Agile environment.

Build modern data and AI analytics solutions using ThoughtSpot, Snowflake, semantic data layers, and governed data assets. Develop ETL processes, AI prompts, intelligent dashboards, and interactive analytics experiences for actuarial teams. Partner with business and analytics stakeholders to support pricing, reserving, underwriting, and portfolio decisions while surfacing trends, explaining business drivers, and enabling actionable recommendations.

Designs, builds, deploys, and sustains enterprise ETL/ELT pipelines using Azure Databricks, SQL, and Python. Responsibilities include batch and streaming ingestion, data transformation, orchestration, quality controls, monitoring, failure recovery, CI/CD, documentation, query optimization, Power BI dataflows, and secure data movement across DoD and Air National Guard systems.

Build and scale the data backbone for HR, payroll, finance, and insurance products. Design data models across warehouses and data lakes, develop and optimize batch and real-time ETL/ELT pipelines, improve data quality and governance, tune SQL queries, address data integration gaps, and collaborate with engineering, BI, analytics, and business stakeholders.

Build and maintain reliable data pipelines, models, lakehouse layers, and analytics-ready datasets using cloud data platforms. The role includes data quality validation, lineage, access management, monitoring, troubleshooting, documentation, stakeholder collaboration, and support for governed enterprise data assets and future AI use cases. Exposure to Microsoft Fabric, Azure services, medallion architecture, Git, CI/CD, and government ICT requirements is advantageous.

Build and maintain scalable data platforms, stores, and ETL/ELT pipelines for structured and unstructured data. Develop software and scripts to retrieve, parse, process, and convert data into usable formats. Support analytics, reporting, monitoring, and platform operations while collaborating with multidisciplinary teams in an agile environment. Work may involve cloud, distributed computing, streaming, NoSQL, and data warehousing technologies.

Build and maintain ETL/ELT pipelines to move product data into analytics-ready stores (Postgres, data lake, warehouse). Design and optimize data models, ensure data quality and documentation, support ad-hoc research requests, and collaborate with research and engineering teams to enable reproducible analytics.

Design, build, and deliver scalable data pipelines and products end-to-end. Partner with analytics, product, and engineering to ingest diverse data sources, implement dbt transformations, ensure data quality, CI/CD, observability, monitoring, and cost/performance optimization. Leverage AI/automation for self-service tooling and intelligent pipelines while driving stakeholder alignment and reliable production operations.

Lead design, develop, test, implement, and support cloud-based data solutions. Collaborate across Agile teams on distributed systems, streaming, data warehousing, and big data tooling. Mentor engineers, perform unit tests and code reviews, and deliver scalable data platforms to support ML and product teams.

Lead Data Engineer designing, developing, testing, and supporting cloud-based data solutions. Collaborate with Agile teams on distributed microservices, machine learning pipelines, data warehousing, streaming, and RDBMS/NoSQL systems. Mentor engineers, review and unit-test code, and deliver performant solutions using cloud and big-data technologies.

Lead architecture and standards for CoreWeave's enterprise data ecosystem: design lakehouse/streamhouse architectures, modeling and semantic layers, governance, data quality, lineage, observability, and reusable data products. Drive cross-domain solutions, resolve performance and scalability constraints, evaluate core data technologies, conduct architecture reviews, and mentor senior engineers.

Builds and maintains scalable data pipelines and cloud infrastructure supporting an AI biomedical research platform. Responsibilities include ingesting, harmonizing, validating, and documenting multimodal neurodegeneration datasets; managing cloud storage, compute, permissions, and costs; implementing de-identification and data governance workflows; supporting research data repositories and AI/ML teams; and maintaining data lineage, catalogs, and technical documentation. The role requires strong Python and SQL skills, software engineering discipline, cloud experience, and neurodegeneration research data expertise.

Responsible for building data models, developing ELT pipelines, implementing data quality checks, and utilizing best practices in data engineering and healthcare analytics.

Designs, builds, and maintains secure cloud data pipelines and centralized repositories; publishes curated datasets; develops WPS AI agents; produces dashboards and visualizations for senior military leadership; supports NATO and annual statutory reporting and prepares technical briefings and deliverables.

Build and maintain ingestion pipelines for heterogeneous healthcare data (TPA feeds, claims, eligibility, enrollment). Design dbt models and orchestration (Dagster/Airflow), implement data quality monitoring and observability, and partner with data science to produce and maintain feature pipelines and feedback loops.

Design, build, and maintain ETL pipelines, databases, and data models to process healthcare claims and related data. Ensure data quality, analyze claims data for trends, and produce reports and visualizations for nontechnical stakeholders. Collaborate with policy and analytics teams to translate requirements into data solutions and improve data infrastructure and analytics capabilities.

Lead hands-on data engineering and architecture for a classified on-prem Analytics Core: build ETL/ELT pipelines, clean and model 30 years of multi-modal and geospatial data, integrate ESRI spatial data, establish AI/ML feature standards, enforce DoD-aligned governance, and mentor transitioning staff to operationalize the solution.

The Data Engineer will design and implement data ecosystems, build data pipelines, and ensure data quality while collaborating with stakeholders and utilizing AWS services.

Build and maintain Power BI reporting for FP&A: extract and transform data (Bronze/Silver), semantic modeling and dashboards (Gold), ensure accuracy, security, performance, and manage Power BI Service access and role-level security.

Build, test, and operationalize complex data pipelines and solutions on cloud platforms. Analyze and transform data, ensure data governance, security, and quality, troubleshoot defects, and collaborate across teams to support analytics, ML/AI, and business intelligence needs.

Design, build, and maintain secure, scalable data pipelines and platforms (including Palantir Foundry/Gotham) for mission-driven clients in classified or restricted environments. Guide cross-functional teams, communicate architecture decisions, implement secure analytics ecosystems, and support AI/ML integration and DevSecOps practices under constrained mission conditions.

Designs and deploys scalable data pipelines, preprocessing workflows, feature-engineering services, and machine learning models for secure DoD environments. The role supports structured and unstructured mission data, exploratory analysis, visualization, model inference APIs, reproducible MLOps workflows, and decision-support capabilities. Responsibilities include collaborating with product, software, platform, DevSecOps, data science, and mission teams; deploying containerized services; participating in Agile delivery; and maintaining technical documentation.