Top Data & Analytics Jobs in Richmond, VA

Leads the data engineering function and manages a team of at least five employees. Owns enterprise data platform execution, scalable pipeline development, Medallion architecture implementation, DataOps, CI/CD, observability, reliability, stakeholder intake, and engineering standards. Partners with data architecture and application teams, mentors engineers, drives delivery, and develops future leaders.

Leads enterprise Workforce Intelligence across Customer Excellence, integrating workforce, operational, quality, customer, and service data into actionable insights. Establishes performance frameworks, executive reporting, governance, root-cause analysis, and reporting automation. Partners with Operations, Workforce Management, Finance, HR, Training, and Technology while leading a global team and driving performance improvements.

Build trusted GTM business intelligence by defining commercial metrics, analyzing performance across Sales, Marketing, Customer Success, Product, and Finance, diagnosing root causes, and delivering executive recommendations. Partner with data engineering and operations teams to integrate Salesforce, product, support, marketing, billing, and financial data. Evaluate AI-powered analytics capabilities and improve self-service decision-making.

Supports TPG’s sustainability analytics team by creating dashboards, automating reporting, improving data processes, and contributing to emissions accounting, regulatory reporting, physical climate risk assessments, and LP engagement. The role requires advanced data visualization, analytics, and reporting skills, along with interest in responsible investing, climate, or sustainability.

Design, build, optimize, and operate enterprise cloud data platforms and Databricks ETL/ELT pipelines. Develop batch and streaming pipelines, data models, infrastructure-as-code solutions, BI dashboards, monitoring, and scalable ML models. Ensure platform reliability, governance, security, and compliance while collaborating with software, systems, product, and business teams.

Staff Data Analyst leading complex, cross-functional analytics initiatives and executive-level decision support. Responsibilities include defining metrics, building scalable data models and infrastructure with dbt, ensuring data quality and governance, developing analytical roadmaps, mentoring analysts, improving data literacy, and advising Sales, Marketing, Finance, and Operations stakeholders.

Leads and scales the Growth Product Insights data practice, managing and mentoring data analysts while contributing hands-on analytical work. The role drives proactive insights, experimentation, causal inference, cohort modeling, KPI development, and strategic recommendations for product and growth leaders. It also strengthens data quality and metric governance, partners with engineering teams on complex pipelines and event data, and integrates modern analytics and generative AI tools into team workflows.

Owns the end-to-end data platform, including Snowflake infrastructure, ingestion pipelines, Airflow orchestration, dbt transformations, governed gold-layer models, and metric definitions. Ensures reliability, performance, testing, documentation, governance, and CI/CD standards. Builds data systems from scratch, partners with analytics stakeholders, and uses AI-assisted development tools to accelerate engineering work. Requires strong SQL, platform ownership, software engineering practices, and experience with Snowflake, Airflow, and dbt.

Leads Antenna’s insights and analytics function, setting editorial standards, managing custom data delivery, building internal tools and workflows, defining KPIs, and hiring and developing a remote analyst team. The role presents findings to senior clients, partners cross-functionally on data products, identifies new analytics opportunities, and remains hands-on with complex analyses. Requires strong leadership, communication, technical SQL and AI knowledge, client engagement, and media industry experience.

Build network capacity and demand forecasts across 50 states, support clinician recruitment and retention analytics, measure clinical and scheduling outcomes, and design experiments with Product and Engineering. Develop governed data models, KPI definitions, and AI-powered analytics infrastructure. Serve as the primary analytics partner for Network leadership by translating complex, multi-source data into actionable recommendations and presenting insights to technical and executive audiences.