Top Data & Analytics Jobs

Lead architecture and delivery of enterprise-scale data platforms, pipelines, and MDM. Integrate agentic AI/LLM workflows, build ML-ready data foundations, set engineering standards, lead cross-team technical initiatives, and mentor senior engineers.

Develop Power BI dashboards, semantic data models, SQL extracts, and scalable reporting solutions while helping build a Microsoft Fabric analytics environment. Partner with leaders across portfolio companies to translate business needs into actionable insights, troubleshoot data quality issues, automate reporting, support integrations, and document data definitions. The role combines hands-on BI development, ad hoc analysis, stakeholder collaboration, and modernization of enterprise reporting.

Drive growth and product decisions through experimentation, statistical analysis, metrics management, data pipelines, modeling, and dashboard development. Partner with business and product teams to answer analytical questions, build ingestion and transformation workflows with dbt, and create visualizations that enable stakeholders to explore data and act on insights.

Leads the creation and scaling of Unitek Learning’s enterprise analytics organization. Defines the operating model, technology stack, analytics roadmap, governance, and reporting capabilities. Oversees campus, competitive, marketplace, and macroeconomic analytics to support forecasting and strategic decisions. Partners with Finance, Operations, and Marketing, while presenting actionable insights to executive leadership and promoting data-driven decision-making and AI adoption.

Supports enterprise data migration initiatives across ERP and system modernization programs. Responsibilities include source-data analysis, cleansing, mapping, transformation, reconciliation, testing, migration execution, defect resolution, reporting, and stakeholder coordination. The role partners with business, technical, and consulting teams to ensure data quality, compliance, and operational readiness throughout mock loads, cutovers, and production deployments.

Conducts QA/QC and detailed analysis of lidar, imagery, elevation, hydrography, terrain, and other geospatial products. Creates derivative data, reports, metadata, documentation, and process improvements; trains junior staff; leads quality meetings; coordinates analysts; represents quality teams with clients; and supports project scope, budget, and resource estimates.

Build and maintain finance data pipelines, warehouse models, dashboards, and automations for unit economics, technology budgeting, burn, runway, margins, deal desk, and sales compensation. Develop internal tools and LLM-based agents that help non-engineers access trusted financial data. Partner with finance, sales, and engineering leadership to reconcile discrepancies and improve revenue, cost, billing, payroll, cloud-spend, and accounting workflows.

Designs, deploys, and optimizes production-grade data infrastructure, ETL/ELT pipelines, distributed databases, streaming systems, vector databases, APIs, and feature stores for AI and machine learning applications. The role also implements data quality, observability, lineage, testing, compliance, and secure cloud-native deployments. As a forward-deployed engineer, the employee partners directly with customers, prototypes solutions, transitions them to production, and feeds field learnings into platform improvements.

Lead and manage a team building and operating enterprise data pipelines, warehousing, and integration solutions. Oversee data architecture, ETL, data quality, governance, BI support, vendor selection, and cross-functional collaboration to ensure reliable, scalable, and secure data for business reporting and decision-making.

Leads BI, analytics, and AI initiatives that transform energy market and customer data into dashboards, automated insights, predictive analyses, and strategic recommendations. The role supports pricing, acquisition, retention, marketing, finance, and customer experience decisions through Python, SQL, Tableau, Power BI, generative BI, experimentation, and machine learning. Responsibilities include building executive reporting, evaluating AI-enhanced BI platforms, analyzing customer lifecycle performance, mentoring analysts, and partnering with cross-functional business and technical teams.