Top Data & Analytics Jobs

Analyze complex datasets, build Power BI dashboards and reports, write SQL, and use Python with Pandas and NumPy for data manipulation and automation. Work extensively with Snowflake, validate and reconcile data, define KPIs, support forecasting and AI-driven analytics, and translate stakeholder requirements into analytical solutions. Present insights and recommendations while collaborating with business, data engineering, and data science teams to improve reporting, data quality, governance, and self-service BI.

Analyzes specialty-products markets, customer pricing, contracts, forecasts, and strategic performance metrics. Maintains pricing tools, supports growth action plans and business planning, manages agreements and nickel hedges, and prepares market and customer reports and presentations. Coordinates with field representatives, product managers, sales teams, and customers to support commercial activities and corporate reporting.

Analyze payment accounts and transactions to identify fraud and credit risk, develop scalable risk strategies, and design solutions including ML features and manual review workflows. Collaborate with Engineering, Product, Data Science, and Operations to mitigate fraud across geographies, payment methods, and products. Educate Stripe users about business risks and prevention strategies.

Senior Business Analyst leading discovery and requirements definition for Data & AI initiatives. Translates business needs into user stories, technical and functional requirements, and acceptance criteria; coordinates stakeholders, data engineers, BI developers, and product owners through delivery. Manages intake, prioritization, sprint progress, and communication while promoting Agile practices, MVPs, process consistency, and data-driven decision-making. Requires experience with analytics environments, Power BI, Tableau, project tracking tools, SDLC, and data concepts.

Build and maintain data pipelines, ETL workflows, integrations, data quality tools, and reporting solutions for freight and logistics operations. Write Python and SQL, troubleshoot data issues, document workflows, collaborate with business teams, and use Git-based development practices. The role includes mentorship and opportunities to develop foundational data engineering skills.

Support GEOINT and Multi-INT production at NASIC by developing structured data schemas, ensuring adherence to intelligence community standards, identifying useful data sources, and maintaining data consistency through QA/QC scripts. Collaborate with analysts, data scientists, engineers, and government stakeholders while providing technical guidance, briefings, and documentation.

Designs and maintains production data pipelines, models claims and operational data, and improves reliability through testing, monitoring, and alerting. Owns workflow troubleshooting, backfills, performance optimization, documentation, access controls, and CI/CD practices. Partners with business and technical teams to define requirements and deliver trusted datasets using SQL, Python, cloud data warehouses, and orchestration tools.

Designs and maintains scalable data pipelines, data platforms, reporting infrastructure, reconciliation systems, and self-service tools. Develops customer-facing and internal applications, integrates external data, improves data quality and auditability, and optimizes near-real-time processing. The role requires collaboration with engineering, analytics, product, data science, and security teams, along with participation in on-call support and technology evaluation.

Leads and mentors a SQL Developer team while designing, developing, optimizing, and securing SQL Server database solutions. Responsibilities include data modeling, T-SQL development, performance tuning, SQL Agent management, SSIS and SSRS integrations, ERP data replication, reporting structures, backups, permissions, HIPAA compliance, and data integrity. The role partners with application, infrastructure, and business teams and supports data lake initiatives such as Snowflake.

Lead PMG’s analytics organization across clients, industries, and regions. Define the analytics capability roadmap, scale teams, guide senior client relationships, and align measurement strategies with business objectives. Oversee attribution, incrementality, reporting, experimentation, and data architecture while partnering cross-functionally. Manage Director-level leaders, succession planning, performance processes, governance, and thought leadership. Use AI, automation, and emerging analytics technologies to improve efficiency, decision-making, and marketing performance.