Senior Data Engineer

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Information Technology Full Time Regular Professional United State, US

Salary Range: $ To $ Annually

Location: United States
Job Type: Full-Time | Exempt | Hybrid/Remote Eligible
Salary Range:$135,000 – $170,000 per year

About Commercial Bank of California

Commercial Bank of California (CBC) is the largest Latino-owned bank in California and a certified Minority Depository Institution (MDI). Headquartered in Irvine and founded in 2003, CBC is one of the largest privately held banks in the state, with over $4 billion in assets as of November 2026.

We are a purpose-driven financial institution committed to building long-term relationships and delivering innovative, personalized banking solutions. Our leadership reflects the diverse communities we serve, and our mission is rooted in empowering entrepreneurs, business owners, and community leaders to thrive.

As a certified MDI, CBC is proud to play a vital role in advancing financial inclusion and economic opportunity. We believe in a higher vision for banking—one that prioritizes trust, collaboration, and community impact. Join us and be part of a team that’s redefining what it means to be a community-focused, relationship-driven bank that puts people over profits.

Job Summary

The Senior Data Engineer is responsible for designing, building, and operating scalable, secure data platforms that power enterprise analytics, reporting, and advanced data use cases, including financial services and payments data. With 7-10+ years of hands‑on data engineering experience, this role serves as a data engineer who can wear an architect hat, owning end‑to‑end data pipelines, data models, and analytical data stores across the Azure ecosystem.

You will lead the implementation of Microsoft Fabric, Azure Databricks, and modern lakehouse architectures, including the migration of Databricks workloads to Microsoft Fabric where it makes sense, while partnering closely with business intelligence, analytics, AI, and business stakeholders. This role emphasizes data reliability, governance, and performance at scale, supporting both operational and strategic decision-making.

Essential Duties and Responsibilities

• Design, build, and maintain enterprise‑grade data platforms using Microsoft Fabric, Azure Data Lake, Azure Synapse, and Azure Databricks.
• Architect and implement lakehouse and medallion architectures (Bronze/Silver/Gold) to support analytics and BI workloads.
• Define standards for data ingestion, transformation, storage, and access across structured and semi‑structured data sources.
• Plan and execute Databricks-to-Fabric migrations, including workload assessment, Delta/One Lake data movement, notebook and pipeline conversion, semantic model re‑pointing, validation, and cutover.
• Develop and optimize batch and streaming data pipelines using Databricks, Fabric Data Pipelines, and Azure‑native services.
• Implement robust ETL/ELT processes, ensuring data quality, accuracy, and consistency across systems.
• Monitor, tune, and optimize data pipelines for performance, scalability, and cost efficiency.
• Integrate and model data from FIS core banking and H360 systems into the lakehouse for analytics and reporting.
• Build and support data pipelines for payments data (e.g., ACH, wire, card, and real‑time payments), including ingestion, reconciliation, and reporting.

Data Modeling & Analytics Enablement

• Design and maintain logical and physical data models optimized for analytics, reporting, and downstream consumption.
• Build semantic models and curated datasets to support Power BI and enterprise Business Intelligence use cases.
• Partner with BI…