Top Data & Analytics Jobs

Leads a small team responsible for enterprise data engineering, data warehousing, database administration, integrations, SharePoint, Nintex automation, Power BI enablement, governance, security, and operational reliability. The role owns Microsoft Fabric and EDW architecture, builds and supports ETL/ELT pipelines, manages platform roadmaps and vendors, applies AI-enabled automation, and partners with IT and business stakeholders to deliver trusted, secure, governed data services.

Designs and maintains scalable data pipelines, warehouse models, and analytics solutions. Builds natural-language data interfaces using GenAI and LLM techniques, optimizes SQL, improves data quality and observability, and supports distributed data platforms on AWS or GCP. Partners with engineering, analytics, business, and product teams, contributes to shared codebases, establishes development standards, and participates in production on-call and incident response.

Develop and maintain SQL-based data views, ETL workflows, and cloud data warehouse processes supporting CMS healthcare research data. Ingest new data sources, optimize database performance, document business logic, support production data loads, and collaborate with analysts, technical leads, and CMS partners. The role also involves data quality, monitoring, permissions, recovery, troubleshooting, and occasional off-hours or weekend production support.

Analyze client performance, KPIs, utilization trends, and operational benchmarks using large healthcare datasets. Build reporting views, dashboards, reusable queries, models, and notebooks for Client Success and Operations. Conduct cohort, benchmarking, root-cause, and network opportunity analyses, then translate findings into clear narratives for executives and clients. Partner with analytics leadership to improve analytical standards, documentation, and reusable frameworks.

Build and lead Crown Castle’s Data and AI Governance Engineering capability. Establish governance, data quality, metadata, lineage, access, observability, and AI governance strategies while automating controls and workflows across Databricks and the broader data ecosystem. Remain hands-on with prototyping, testing, troubleshooting, and reusable engineering patterns. Partner with technical, legal, security, risk, audit, architecture, and business teams to improve data trust, accountability, discoverability, and responsible AI adoption.

Build and operate production data pipelines and enterprise data services supporting AI models, agents, and mission applications. Integrate structured and unstructured data across relational, document, vector, and graph systems; establish data quality, lineage, metadata, governance, and secure access practices; and collaborate with AI, platform, government, and commercial engineering teams. Deploy services in Kubernetes and classified environments while developing reusable ingestion, orchestration, documentation, and operational patterns.

Analyzes datasets to identify trends and insights supporting organizational decisions. Develops and manages data sources for demand and capacity planning, source and supply planning, process efficiency, and quality management. Uses Microsoft tools and visualization platforms such as Power BI, Qlik Sense, or Tableau. Requires strong analytical, organizational, communication, and time-management skills, with the ability to manage multiple priorities and work independently.

Build and operate production data integrations and ETL pipelines using AWS Glue, PySpark, Python, SQL, and ClickHouse. Responsibilities include designing schemas, integrating unfamiliar data sources, monitoring pipeline health, debugging incidents, improving observability, supporting restricted-environment deployments, and participating in on-call operations. The role collaborates with forward-deployed engineers and requires full-time onsite work in New York City, occasional travel to Arlington, and eligibility for a U.S. government security clearance.

Leads data engineering, business intelligence, and analytics teams; oversees data pipelines, integration infrastructure, database architecture, CI/CD practices, and enterprise data platform strategy. Partners with business and technology stakeholders to define requirements, improve data capabilities, maintain Ubuntu-based services, and deliver reporting and KPIs to leadership. Responsible for team hiring, development, mentoring, operational health, and technical execution across analytics and data integration platforms.

The Media Data Analyst will enhance Media datasets, oversee data extraction and transformation, and collaborate with clients and teams to improve product features.