Top Data & Analytics Jobs

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.

Analyzes operational performance and financial-impact data for Philadelphia’s Water Department. Responsibilities include acquiring and cleaning large datasets, building data models and views, applying statistical and machine learning methods, identifying patterns, automating predictive and prescriptive analytics, and communicating insights to stakeholders. The role supports resource allocation, asset management, leak detection, water-loss mitigation, and revenue integrity. It requires onsite work, Philadelphia residency, off-hours availability, and participation in an on-call rotation.

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.

Administers and supports organizational databases within the IS Data Management team. Diagnoses application, system, and workload performance issues; manages user data access and database authority; reviews database development; conducts performance and volume testing; coordinates with vendors; and reports project progress to stakeholders.

Build and scale Granola’s business data foundation by improving data ingestion, dbt modeling, quality monitoring, documentation, and metric definitions. Create trusted datasets, dashboards, and analyses that support Finance, Go-to-Market, and company leadership. Partner with functional leaders to translate ambiguous business questions into clear technical requirements, actionable insights, and recommendations.