Top Data & Analytics Jobs

Develop and maintain interactive dashboards, reports, scorecards, data models, and visual analytics solutions for a U.S. Navy weapon system program. Connect and optimize diverse data sources, implement calculations and row-level security, manage refreshes and data quality, document data lineage, and translate complex datasets into actionable visual narratives for technical and executive stakeholders.

Develop and implement data engineering, analytics, visualization, and pipeline solutions supporting U.S. Navy weapon-system systems engineering. Responsibilities include data modeling, business process mapping, technical analysis, trade studies, documentation, testing, customer engagement, and COTS/GOTS solution implementation. The role coordinates internal technical teams and Navy customers, evaluates design changes, resolves issues, and supports quality management and lifecycle processes.

Leads an analytics team supporting commercial aviation aftermarket strategy. Oversees enterprise dashboards, forecasts, analytical models, data governance, KPI development, market intelligence, business cases, and strategic opportunity analysis. Manages request prioritization, quality assurance, delivery timelines, team capacity, hiring, coaching, and performance. Partners with business development and program teams to translate aerospace data and market trends into regional growth strategies and executive recommendations.

Leads a team responsible for data engineering platforms, pipelines, schemas, governance, databases, transformations, data marts, and production operations. Sets technical direction, manages architecture and delivery priorities, mentors and hires engineers, and partners with stakeholders. The role requires hands-on involvement in data platform design, PostgreSQL optimization, orchestration, reliability, security, and analytical data serving. It also manages project plans, staffing, budgets, performance measures, and cross-team technical delivery.

Develop and maintain Power BI dashboards, data models, ETL processes, data validations, and automated analytics solutions. Translate stakeholder needs into technical specifications, improve operational efficiency, document BI environments, and support teams across facilities, finance, strategic planning, and project management with trusted data insights.

The Data Governance Specialist partners with business stakeholders to define governance requirements, ownership models, policies, and standards. The role designs stewardship, issue remediation, and metadata approval workflows; configures Collibra operating models, metamodel extensions, and workflows; develops governance frameworks; and leads training and change management. This position translates business needs into scalable technical roadmaps and supports adoption of data governance practices across the organization.

Executes technical data governance, data quality, metadata management, and Collibra administration. Performs data profiling, implements quality rules, maintains metadata lineage and asset diagrams, reports on quality metrics, and supports incident root-cause analysis. Requires strong SQL, Collibra, and data quality tooling experience, with preferred API integration and cloud data environment experience.

Develop and maintain Master Data Management, data governance, stewardship, quality, and reference data processes. Partner with enterprise stakeholders and governance groups to define standards, validate master data, establish quality rules, support data owners, and prioritize initiatives. Lead requirements for system configuration changes while using data profiling, modeling, and analytics to improve data validity and consistency across systems.

Develop and maintain master data management and integration capabilities, including data quality rules, governance processes, stewardship workflows, data validation, profiling, modeling, and integration design. Collaborate with enterprise stakeholders, data owners, stewards, and governance groups to define requirements, configure systems, and support strategic MDM initiatives. Use Python, SQL, AWS services, APIs, Dataiku, and ETL/MDM tools to improve data accuracy, consistency, transformation, and retention.

The Data Engineer will design data models, build data warehouses and lakes, automate data pipelines, and enable data accessibility while maintaining security standards in a complex environment.