Top Data & Analytics Jobs in Richmond, VA

Analyze user behavior, feature adoption, and retention across a B2B SaaS platform to generate evidence-based product insights. Track journeys, run cohort and funnel analyses, support A/B testing, define product KPIs, ensure data accuracy, and provide structured recommendations to inform roadmap and improve adoption and retention.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Architect, build, and maintain Snowflake-based ELT pipelines and production data models. Implement observability, data quality, and governance; optimize cost and freshness. Partner with Analytics, Product, and Engineering, use dbt/CI-CD and AI-assisted tooling, and participate in reviews and architecture planning to support analytics, BI, and ML.

Senior Power BI developer responsible for building dashboards, scorecards, and analyses that deliver actionable insights. Partner with stakeholders and data architecture to join disparate datasets, ensure data quality, perform ETL, apply advanced DAX/Power Query and SQL, and present recommendations to senior leadership to drive KPI improvements.

Analyze IVR caller behavior using SQL and Excel, build Tableau reports to visualize trends, collaborate with stakeholders to improve IVR user flows, and provide data-driven recommendations to enhance caller experience.

Operate and own real-time, petabyte-scale streaming pipelines (Pub/Sub/Kafka, Dataflow/Beam), integrate LLMs/Vertex AI enrichment, build monitoring/alerting, respond to incidents, ensure data integrity, and collaborate with Product and Analysts to improve observability and reliability.

Own pipeline reporting, revenue forecasting, pricing and deal-analysis frameworks, retention/renewal reporting, and marketing performance analysis. Create automated dashboards, partner with sales and engineering to maintain data pipelines, and present insights to commercial stakeholders to drive revenue growth.

Design, analyze, and document data products and technical specifications. Perform large-scale data profiling and SQL analysis, support data governance, partner with stakeholders to remediate issues, and help implement data quality, lineage, and ingestion standards.

Lead the RevOps analytics function: manage an analytics team, own revenue reporting and forecasting, build measurement frameworks, enforce data governance, partner with BI/engineering, analyze funnel and retention metrics, and embed AI/automation to improve revenue predictability and GTM performance.

Design, build, and operate secure, scalable cloud-native data platforms (lakehouse/data mesh) supporting batch, streaming, ML, GIS and operational workloads. Lead ingestion/transformation pipelines, distributed processing (Spark/Kafka), data governance, observability, and mentor teams while ensuring compliance in regulated environments.