Data Engineer

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Full Time Regular Irvine, Irvine, CA, US

7 days ago Requisition

Salary Range: $ To $ Annually

Location: Irvine, CA
Job Type: Full-Time | Exempt | Hybrid Eligible
Salary Range:$150,000 – $170,000 per year

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 $3.5 billion in assets as of December 2025.

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.

The Data Engineer is responsible for designing, building, and operating modern, scalable, and governed data platforms that enable enterprise analytics, reporting, and advanced data use cases. With 10+ years of hands‑on data engineering experience, this role acts as a senior individual contributor and technical leader, owning data architecture, pipelines, governance, and analytics‑ready data models across cloud platforms.

This role has a strong emphasis on analytics engineering, ensuring that data is not only ingested and processed, but modeled, curated, and governed for high quality business intelligence and analytical consumption. You will work extensively with Microsoft Fabric, Azure Databricks, Unity Catalog, and lakehouse technologies.

• Architect and maintain enterprise‑scale data platforms using Microsoft Fabric, Azure Data Lake, Azure Synapse, and Azure Databricks.
• Design and implement lakehouse architectures and analytics‑optimized data layers to support BI, self‑service analytics, and advanced reporting.
• Define platform standards for data ingestion, transformation, storage, and analytics consumption across the organization.
• Build, optimize, and operate reliable batch and streaming data pipelines using Databricks, Fabric Data Pipelines, and Azure‑native services.
• Implement scalable ETL/ELT frameworks with strong data quality, validation, and observability.
• Ensure pipelines are resilient, performant, and cost‑efficient in production environments.
• Design and maintain analytics‑ready data models (star, snowflake, and dimensional models) to support Power BI and enterprise BI use cases.
• Develop curated, trusted datasets and semantic layers that enable consistent metrics and reporting across the business.
• Partner closely with analysts, BI developers, and business stakeholders to translate analytical requirements into scalable data solutions.

• Implement and manage Databricks Unity Catalog for centralized data governance, lineage, access control, and auditing.
• Enforce best practices for data security, role‑based access, and data classification across platforms.
• Ensure compliance with enterprise data governance and regulatory requirements.

• Design and manage CI/CD pipelines for data engineering workloads using Azure Dev Ops.
• Apply best practices for version control, automated testing, environment promotion, and deployment.
• Monitor production data systems to ensure high availability and operational stability.
• Experience in databricks asset bundles (DAB) is preferred.
• Work across modern analytics ecosystems, integrating Azure‑based platforms with other cloud data technologies as needed.
• Leverage experience with Snowflake (architecture, data modeling, performance…