Data Engineer, Finance Data & BI

Responsibilities

• Tackle end-to-end data engineering challenges across the stack, from advanced data wrangling with SQL, Python, Spark, or equivalents to delivering production‑grade data products for stakeholders
• Architect new data systems and rework existing architectures, refining data models, relational schemas, and database logic
• Build, validate, and operate scalable ETL/ELT pipelines on modern cloud platforms that enable advanced analytics and AI/ML workloads
• Create and sustain database code, including stored procedures, functions, and performance‑optimized transformations
• Establish and maintain ETL workflows and contribute to CI/CD deployment pipelines using GitHub Actions or similar tooling
• Implement and optimize data models, such as dimensional modeling, within the Finance data environment
• Tune data architecture for performance, scalability, and cost efficiency across large financial datasets
• Design automated data quality checks, anomaly detection, and validation processes to ensure accuracy for downstream analytics and AI use cases
• Ensure data solutions comply with financial governance and SOX requirements
• Collaborate with Finance teams (Accounting, FP&A), BI, and Data Product partners to translate complex business requirements into scalable technical solutions
• Communicate technical concepts clearly to non‑technical stakeholders, balancing innovation with risk controls
• Enable trusted data environments required for forecasting models, scenario planning, and AI‑driven insights
• Contribute to the strategic evolution of the Finance data platform by evaluating and piloting emerging tools and technologies

Requirements

• 4+ years of relevant data engineering experience
• 4+ years of hands‑on experience as a Data Engineer
• 4+ years of experience with data warehouses, cloud platforms, relational databases, and data visualization or dashboarding tools
• 4+ years handling structured and unstructured data in batch and real‑time processing environments
• Strong proficiency in object‑oriented languages such as Python, Java, or C#
• Demonstrated experience with Google Cloud Platform (GCP) preferred; familiarity with Snowflake, Databricks, Microsoft, or Teradata is a plus
• Proven enterprise experience building and optimizing cloud‑based data solutions, supporting business‑critical systems, and designing or supporting production‑scale AI/ML data pipelines
• Experience with data governance by design, data warehousing and ETL best practices, and CI/CD with GitHub

Technologies

• SQL
• Python
• Spark
• Google Cloud Platform (GCP)
• GitHub Actions
• GitHub
• Matillion
• PySpark
• Oracle JD Edwards
• Snowflake
• Databricks
• Teradata
• Java
• C#

Benefits

• Base pay range: $106,500 - $177,500 per year
• Annual bonus or long‑term incentive opportunities may be offered

Hybrid Expectations

• This position is based in Richmond, VA with a hybrid schedule requiring 3 to 5 days in the office each month
• Candidates must currently reside within a reasonable commuting distance (within 60 miles of Richmond)
• Relocation assistance is not available for this role

Compensation

• Base salary: $130,000 to $140,000
• 10% Annual Incentive