Top Data & Analytics Jobs

Designs, builds, validates, and maintains governed analytical data models, curated datasets, and reporting layers. Translates business requirements into data mappings, transformation logic, and reusable BI datasets. Develops SQL and dbt tests, performs data reconciliation and root-cause analysis, optimizes Snowflake models, and supports dashboards, reports, UAT, and regulatory extracts. Collaborates with stakeholders, data engineers, architects, analysts, and business teams across insurance and corporate functions.

Supports enterprise data governance and business intelligence initiatives by profiling datasets, defining quality rules, validating metadata and lineage, maintaining business glossaries, and testing API integrations. Develops data-quality scorecards, governance reports, dashboards, documentation, and training materials. Collaborates with data owners, stewards, engineers, and government stakeholders while tracking remediation and testing evidence in Azure DevOps. The role requires Power BI, data governance, data-quality, SQL, ETL, and relational database experience in a Navy environment.

Leads qualitative and quantitative market research programs from proposal through presentation, combining survey design, statistical analysis, qualitative synthesis, AI-enabled analytics, and dashboard development. Manages client relationships, identifies business opportunities, presents strategic insights, and supports account growth. Collaborates with public relations, marketing, creative, and strategy teams while overseeing research staff and projects.

Build and operate scalable data pipelines and platforms that transform LiDAR, imagery, and GPS sensor data into reliable geospatial deliverables. Responsibilities include automating ingestion, AI processing, quality checks, monitoring, workflows, and data access; partnering with Data Operations and GIS teams; and improving AWS processing performance and cost. The role requires end-to-end ownership, including system design, operation, and on-call support.

Analyze adoption, usage, colleague experience, sentiment, and business impact data to support firm-wide transformation initiatives. Build and maintain Power BI dashboards, automated reports, and performance monitoring solutions. Conduct deep-dive analyses, optimize reporting processes, and translate complex data into executive-ready insights and recommendations. Collaborate with global stakeholders across functions and organizational levels to measure program outcomes and identify improvement opportunities.

Develop, administer, and support Power BI, Azure, Fabric, and cloud analytics solutions. Build semantic models, reports, dashboards, database objects, and automation; monitor platform capacity, performance, reliability, and costs. Partner with engineering, business, and project teams to define requirements, deliver projects, support users, and improve BI operations. Establish standards and best practices in an Agile/Scrum environment while enabling scalable, AI-supported analytics solutions.

Leads and scales Scribd’s Analytics Engineering organization, building high-performing teams and governed data foundations for AI-driven decision-making. Oversees canonical data models, semantic layers, quality, observability, documentation, security, lineage, and platform standards. Partners with engineering and business leaders to guide architecture, prioritize investments, and deliver reliable data products with measurable impact. Requires strong technical judgment, advanced SQL, modern data stack experience, cross-functional leadership, and 10+ years of relevant experience.

Designs and manages advanced analytics models and reporting tools for supply chain, inventory, fulfillment center labor, and operational performance. Builds predictive analytics to forecast key metrics, automates reporting, provides data-driven decision support, collaborates with cross-functional teams, and mentors entry-level analysts.

Manages program data by cleaning, updating, validating, and preparing datasets for analysis. Monitors data integrity across systems, resolves collection issues, identifies data-quality trends, supports visualizations and form configuration, and maintains documentation. Collaborates with stakeholders on project and platform maintenance activities while adapting to changing priorities. Requires R data manipulation, basic descriptive statistics, online survey-form development, digital fluency, strong attention to detail, and independent task management.

Lead ownership and evolution of a Microsoft Fabric-based data platform: design medallion/semantic architectures, build and optimize data pipelines, enable Power BI reporting, support SQL Server performance and API integrations, implement observability with Azure Log Analytics/KQL, and shape the data+AI roadmap.