Top Senior Data & Analytics Jobs in Richmond, VA

Own and evolve Worldly’s production data lake, Postgres warehouse, CDC and streaming pipelines, dbt transformations, orchestration, BI access controls, and graph integrations. Maintain reliable, governed analytics infrastructure using Iceberg, Trino, Dagster, Terraform, and AWS. Support production generative AI workflows involving embeddings, similarity search, extraction, and classification. Responsibilities include data quality, monitoring, security, incident response, disaster recovery, schema governance, and collaboration with data science and analytics stakeholders.

Leads advanced analytics initiatives supporting sales, marketing, and operations strategy. Develops statistical and predictive models, dashboards, KPI reporting, and customer analyses using large datasets. Partners with stakeholders and data engineering teams to translate business questions into actionable insights, communicates findings to executives, and mentors junior analysts.

Develops and automates complex sales reports and dashboards using Power BI, SQL, SSRS, SSIS, Excel, and related tools. Performs data transformation, cleansing, modeling, analysis, reconciliation, and integrity controls. Serves as a reporting subject matter expert, supports partners and leadership, resolves reporting escalations, mentors analysts, and contributes analytics to revenue-growth initiatives.

Architect and maintain NetBrain’s first cloud data warehouse, ELT pipelines, transformation layer, semantic models, and BI foundation. Own data quality, governance, lineage, access controls, and curated models supporting product usage, customer adoption, account health, and go-to-market reporting. Partner with stakeholders to establish reliable metrics and a standardized source of truth, while supporting AI-assisted analytics and natural-language reporting use cases.

Leads enterprise data strategy, platform architecture, Master Data Management, federated governance, data quality, compliance, and real-time analytics. Builds scalable data infrastructure, modernizes legacy pipelines, establishes operational data hubs, and enables secure data products across the enterprise. Oversees data engineering, architecture, MDM, governance, and embedded analytics teams while partnering with executives and business units to drive transformation, operational efficiency, AI readiness, and acquisition integration.

Build and maintain data models, pipelines, metrics, dashboards, and analytics supporting identity graph construction, entity matching, and identity resolution. Partner with engineering and data science teams to productionize matching logic, evaluate match quality, monitor data quality and drift, and manage identity-provider relationships. Translate complex identity concepts into actionable insights for technical and non-technical stakeholders while helping define privacy-conscious product and data priorities.

Design and lead scalable, secure, highly available database infrastructure for multi-terabyte SQL Server environments. Set technical direction for data architecture, performance, real-time pipelines, security, and growth. Troubleshoot complex production issues, optimize queries and indexes, guide cross-functional projects, mentor engineers, review changes, reduce technical debt, and evaluate emerging technologies. Monitor database health using Splunk, Datadog, and Grafana while influencing engineering and Site Reliability strategy.

Design, build, and own scalable data pipelines and warehousing architecture from ingestion through analytics and incentive payouts. Lead data platform architecture, dbt modeling, data quality, lineage, observability, performance, and cost management. Partner with engineers and analysts on telematics accuracy and driver incentive reporting. Use AI coding tools daily to develop and review pipelines, SQL, and data models.

Manages a data engineering team responsible for scalable, reliable data pipelines, infrastructure, and analytics tooling. Provides mentorship, performance management, and technical leadership while coordinating with product, analytics, finance, compliance, engineering, and regulators. Prioritizes cross-functional projects, supports data architecture and governance, ensures performance and reliability, and operates within strict regulatory and audit requirements.

Own the company’s data function by designing and optimizing Snowflake architecture, pipelines, integrations, data models, BI dashboards, metric definitions, governance, and data-quality standards. Partner with leadership and cross-functional teams to translate operational needs into trusted data products. Automate recurring reporting, troubleshoot ingestion issues, perform ad hoc analysis, and establish scalable analytics practices as the first dedicated analytics hire.