Senior Data Engineer (Databricks) - Finance Data Modeling

Job summary

Build and own a Databricks finance data platform, including scalable ELT pipelines and trusted, reconciled models for general ledger, sub-ledger, and financial reporting data. Create governed, reporting-ready data layers; productionize and optimize workloads; and mentor engineers while establishing team standards.

Job details

Current contract is for 3 months of work and likely extend to 4 with more conversations later on to extend the contract even longer (this is a large program at RBC) ****************If someone is currently working/if need be we can offer a 6 month contract as if this doesn't extend we'd likely have other work to transition them to. Senior Data Engineer — Databricks & Finance Data About the role We are hiring a Senior Data Engineer to build and own the finance data platform on Databricks. You will design the pipelines and data models behind the general ledger, sub-ledgers and financial reporting, turning raw data into trusted, reconciled datasets that Finance, FP&A and leadership rely on for close, reporting and planning. What you'll doDesign and build scalable ELT pipelines on Databricks (PySpark, Spark SQL, Delta Lake) that ingest data from finance systems Model core finance data: general ledger, chart of accounts, journal entries, trial balance, sub-ledgers (AP, AR, fixed assets), cost centres, legal entities and intercompany. Build curated, reporting-ready layers using a medallion architecture (bronze, silver, gold) and dimensional modelling (star schemas, conformed dimensions, slowly changing dimensions). Implement governance with Unity Catalog Orchestrate and productionize workloads with Databricks Workflows or Airflow, CI/CD and infrastructure-as-code. Tune performance and cost across clusters, SQL warehouses and Delta tables. Mentor engineers, review code and set modelling and engineering standards for the team. What you bring7+ years in data engineering, including 3+ years building production workloads on Databricks. Proven experience modelling finance data. Strong Python/PySpark and advanced SQL; deep working knowledge of Delta Lake. Solid dimensional modelling skills (Kimball) and experience with medallion architectures. Experience building data quality and reconciliation controls in a regulated or audited environment. Hands-on with a major cloud platform (Azure, AWS or GCP), Git-based CI/CD and orchestration tools. Clear communicator who can work with finance leaders as comfortably as with engineers. Nice to haveDatabricks certification (Data Engineer Professional or Associate). Experience with dbt, Delta Live Tables or Lakeflow pipelines.

What you’ll do

Build and own a Databricks finance data platform, including scalable ELT pipelines and trusted, reconciled models for general ledger, sub-ledger, and financial reporting data. Create governed, reporting-ready data layers; productionize and optimize workloads; and mentor engineers while establishing team standards.

Requirements

Requires 7+ years of data engineering experience, including 3+ years building production Databricks workloads, with proven finance data modeling experience. Candidates should have strong Python/PySpark and SQL skills, Delta Lake and dimensional modeling expertise, experience with data quality controls in regulated or audited environments, and familiarity with cloud platforms, CI/CD, and orchestration.

Listed skills

• CI/CD · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Databricks
• PySpark
• Spark SQL
• Delta Lake
• Python
• Advanced SQL
• Finance Data Modeling
• Dimensional Modeling
• Medallion Architecture
• Unity Catalog
• Databricks Workflows
• Airflow
• CI/CD
• Infrastructure as Code
• Data Quality and Reconciliation
• Cloud Platforms

Job areas

• Data & Analytics
• Technology
• Finance & Accounting
• Software

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