Top Data & Analytics Jobs

Leads the strategy, architecture, and execution of an enterprise data platform supporting analytics, machine learning, operational systems, and AI applications. Manages and mentors data platform engineers while remaining hands-on with architecture, reliability, technical direction, and troubleshooting. Oversees pipelines, orchestration, governance, security, observability, data contracts, migrations, and platform operations. Partners cross-functionally to translate business needs into scalable technical solutions and communicates decisions to technical and non-technical stakeholders.

Design and implement data pipelines, ensuring data movement, transformation, storage, availability, and scalability for AI/ML and mission applications. Collaborate with software engineers and data scientists using Databricks, AWS, ETL processes, relational databases, and Agile Scrum. Build solutions supporting defense and intelligence customers, including data-driven dashboards and deployments across JWICS, NIPR, and SIPR environments.

Design, build, and optimize modern Azure and Databricks data platforms for clients. Develop batch and streaming ingestion pipelines, lakehouse and medallion architectures, dimensional models, and transformation workflows. Lead discovery sessions, requirements workshops, architecture discussions, and solution reviews. Recommend practices for governance, lineage, monitoring, DevOps, security, and data modeling while translating business needs into scalable technical solutions and communicating with technical and executive stakeholders.

Designs and maintains scalable data pipelines, architectures, ETL processes, data models, and governance frameworks for secure DoD analytics and AI initiatives. Integrates complex data sources, ensures data quality and compliance, and supports deployment and sustainment of data platforms. Collaborates with data scientists, product managers, and mission stakeholders to deliver operational decision-support solutions.

Build and validate SQL transformations mapping healthcare financial and clinical data into a unified ontology and semantic layer. Reverse-engineer customer business rules, own testing and data correctness, manage historical backfills and incremental loads, and collaborate with customers and platform, insights, and product engineering teams. The role requires strong healthcare revenue-cycle data expertise, production Python, modern data-platform experience, transformation-as-code workflows, data modeling, and customer-facing requirements discovery.

Provides portfolio analytics, financial insights, resource and capacity analysis, executive reporting, dashboards, applications, automation, and process improvements. The role consolidates data from multiple enterprise systems, identifies portfolio trends and risks, supports investment and planning decisions, and translates complex information into clear leadership narratives. It is a senior individual contributor role without responsibility for project oversight, governance authority, or people management.

The Analytics Engineer will develop data models, build dashboards, ensure data reliability, optimize workflows, and foster collaboration to enable data-driven decisions in healthcare operations at Alaffia.

Builds scalable business intelligence solutions, including databases, data warehouses, queries, dashboards, and automated reports. Translates business requirements into actionable data solutions, integrates BI platforms with enterprise systems, manages data transfers, troubleshoots data quality and performance issues, and supports testing, documentation, vendor coordination, and end-user training.

Leads data engineering strategy, architecture, delivery, support, and lifecycle management for secure, scalable cloud and hosted data solutions. Collaborates with technical and business stakeholders to deliver complex datasets, establish enterprise data standards, manage data engineering teams, and oversee maintenance, change management, capacity planning, business continuity, disaster recovery, and regulatory security requirements. The role also evaluates third-party tools and supports Azure DevOps, SDLC, CI/CD, and technical innovation.

Leads data engineering for Payment Operations monitoring transformation. Designs and maintains Snowflake pipelines, tables, stored procedures, monitoring scenarios, KPI infrastructure, and data quality controls. Serves as the Snowflake subject matter expert, documents architecture and operational processes, guides technical partners, and translates business needs into scalable data solutions. The role requires production data engineering experience, advanced SQL, Snowflake expertise, job scheduling, pipeline operations, and stakeholder communication.