Top Data & Analytics Jobs in Richmond, VA

Architects and leads enterprise data engineering platforms, including scalable ETL/ELT pipelines, streaming frameworks, cloud infrastructure, data warehouses, and AI/ML data systems. Establishes engineering standards, governance, monitoring, data quality, security, and schema management practices. Designs AI agents using LLMs, partners across business and infrastructure teams, and makes high-impact architectural decisions for reliable, secure, multi-region data environments.

Analyzes complex program data across Family and Youth Peer Support Services, ensuring data quality, managing reporting systems, developing dashboards and performance reports, identifying trends, and delivering actionable insights. The role coordinates cross-site reporting, supports data collection and process improvement, presents findings to leadership and external stakeholders, and provides technical guidance and training to program staff.

Designs, builds, secures, monitors, and supports scalable data platforms across public and multi-cloud environments. Develops batch and streaming pipelines, ELT processes, data lakes, warehouses, APIs, and integrations with transactional systems. Works with SQL and NoSQL databases and technologies including Spark, Hadoop, Databricks, Snowflake, Kinesis, and Lambda. Leads projects, presents to leadership, collaborates with clients and Scrum teams, troubleshoots issues, and enables analytics and machine learning initiatives.

Designs and oversees enterprise data architectures spanning databases, warehouses, lakes, integrations, and cloud environments. Translates business requirements into scalable, secure, and cost-efficient solutions; establishes data modeling, governance, quality, metadata, and security practices; guides engineers and analysts; optimizes infrastructure; and maintains architecture documentation. Requires extensive Databricks, data engineering, big data, cloud, and stakeholder leadership experience.

Lead data strategy and execution for emerging sectors, transforming large consumer datasets into accurate, scalable client insights. Responsibilities include resolving data-quality issues, designing workflows, maintaining sector taxonomies, partnering with product, revenue, engineering, and insights teams, and coaching analysts. The role requires hands-on analysis, production-grade data workflow development, stakeholder communication, and ownership of quality standards and methodologies in a rapidly evolving environment.

Analyzes business and system requirements, translates them into functional designs, and supports technology enhancements and quality initiatives. Collaborates with stakeholders on project scope, timelines, testing, demos, and implementation. Monitors system usage, investigates errors and exceptions, assists with UAT, tracks project progress, communicates risks, and serves as a technology subject matter expert within the mortgage and secondary market domain.

Own and evolve UJET’s data platform, including MySQL CDC replication to BigQuery, dbt transformations, Terraform infrastructure, pipelines, data quality, observability, and Looker models. Build reliable, analytics-ready datasets and trusted metrics for internal and customer-facing reporting. Partner with Analytics, Finance, Product, and Engineering to deliver scalable data solutions, improve platform reliability, optimize performance and costs, and establish development standards and guardrails.

Design, implement, and maintain data pipelines, integrations, and data architecture using Snowflake and related tools. Support insurance-sector consulting engagements by analyzing data, developing solutions, troubleshooting engineering issues, and presenting recommendations to clients. Collaborate with cross-functional stakeholders, apply data governance and quality practices, and contribute to multiple initiatives. The role requires consulting experience, financial services knowledge, strong communication, and travel of up to 75%.

Supports real-time media monitoring, stakeholder insight analysis, data preparation, alerts, briefings, and client reports. Responsibilities include tracking news across platforms, creating Excel pivot tables, updating charts and graphics, interpreting reputation-risk scoring, conducting research, and translating data into clear narratives. The intern collaborates with analysts to identify trends and emerging risks while developing analytical, writing, and business intelligence skills.

Analyze product, program, member, client, and operational data using advanced SQL in Databricks. Define KPIs and measurement frameworks, conduct segmentation and root-cause analysis, validate datasets, develop reporting, and translate findings into actionable recommendations. Partner with Product, Engineering, Operations, Client Success, and business leaders to improve performance and support strategic decisions.