Top Senior Data & Analytics Jobs

Conducts Army real-property evaluations, GIS and workflow analyses, data reconciliation, and process-improvement assessments. Develops SOPs, manuals, reports, briefings, training plans, and data-driven recommendations. Analyzes HQIIS and related relational-database information, including object models, data models, and metadata repositories. Coordinates with GIS, real-property, business-intelligence, quality, training, and project-management personnel while supporting audits, inventories, data-quality initiatives, and installation engagements.

Build a greenfield data platform and unified Lakehouse integrating high-volume payment, marketing, and operational data across AWS and GCP. Design ingestion pipelines, create dbt medallion-layer transformations in BigQuery, and own Airflow orchestration, lineage, backfills, retries, alerting, infrastructure as code, and cost controls. The role requires autonomous ownership in a fully remote, asynchronous environment, with data mesh and Starburst Galaxy experience as preferred qualifications.

Lead design and execution of a customer experience measurement framework combining quantitative and qualitative data. Analyze trends, provide actionable insights, monitor initiative impact, mentor a team, and partner with cross-functional leaders to improve customer satisfaction and operational processes.

Design, build, and deploy analytics architecture and ETL to process telemetry from hardware and software. Create analysis‑ready datasets, dashboards, alerts, and data products. Apply statistical and ML techniques to improve platform reliability and performance. Lead data‑driven projects with hardware and software teams to inform engineering and leadership decisions.

Lead-level analyst who designs, develops, and delivers reports, dashboards, and data solutions (SQL, Power BI, SSRS, Excel). Analyzes complex healthcare, financial, and operational data, ensures data quality and ETL processes, mentors analysts, manages analytics projects, drives automation and process improvements, and presents insights to leadership and stakeholders.

Design, operate, and scale end-to-end data infrastructure and pipelines. Build reusable data models and a semantic layer, ensure data quality and privacy, implement observability and SLAs, support marketing and growth feeds, partner with cross-functional stakeholders, and enable ML/AI consumption and reverse ETL workflows.

Designs and maintains healthcare data pipelines, ETL workflows, databases, data models, and analytical frameworks. Analyzes claims and payer data to identify trends and insights, while ensuring data quality and integrity. Creates reports, dashboards, and visualizations for nontechnical stakeholders and collaborates with healthcare policy experts, analysts, and other stakeholders to translate requirements into data solutions. The role also improves data infrastructure and analytics capabilities.

Lead data architecture for projects and data products by translating business requirements into scalable solution designs. Create architecture diagrams, data models, pipeline designs, decision trees, reusable frameworks, and standards. Evaluate scope, timelines, costs, trade-offs, and business value; lead proofs of concept; guide engineering and infrastructure teams; participate throughout the SDLC; mentor technical resources; and promote adoption of enterprise data architecture and Lakehouse solutions.

Lead the architecture and evolution of enterprise-scale data platforms, applying distributed-systems and advanced data-modeling patterns. Establish technical standards across dbt, Airflow, Snowflake, Kafka, ETL, cloud infrastructure, security, monitoring, CI/CD, testing, and source control. Solve complex data problems, partner with senior leaders, provide technical governance, mentor engineers, and drive platform and process improvements.

Lead development and execution of enterprise data governance strategies for USMS, improving discoverability, interoperability, metadata management, data quality, lineage, classification, and compliance with federal data mandates while advising senior leaders.