Data Engineer

Commercial Bank of California•Irvine, CA

12d•$150,000 - $170,000•Hybrid

About The Position

The Data Engineer joins Commercial Bank of California’s Enterprise Technology Services team to lead the design, development, and optimization of modern, scalable data platforms for enterprise analytics and business intelligence. This is a senior individual-contributor role requiring more than 10 years of data engineering experience, with ownership of end-to-end data architecture spanning ingestion, transformation, modeling, and governance. The role emphasizes analytics engineering: curating and governing data so it supports high-quality business intelligence and advanced analytics. The engineer works extensively with Microsoft Fabric, Azure Databricks, Unity Catalog, and lakehouse architectures to establish a reliable, scalable, analytics-ready data foundation. The position is based in Irvine, California, and is hybrid eligible.

Requirements

10+ years of experience in data engineering, analytics engineering, or data platform development.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
Hands-on experience with Microsoft Fabric, including Lakehouse, OneLake, Data Pipelines, and Semantic Models.
Hands-on experience with Azure Databricks, including Unity Catalog.
Experience with data modeling for analytics and business intelligence.
Experience with Azure DevOps, including CI/CD, Git, and automated deployments.
Experience with business intelligence platforms, especially Power BI.
Advanced proficiency in SQL and strong experience with Python and Spark-based development.
Proven ability to deliver analytics-ready, production-grade data solutions.
Legal authorization to work in the United States at the time of hire; employment sponsorship is not available.

Nice To Haves

Master’s degree.
Experience with Snowflake, including data modeling, analytics workloads, architecture, and performance tuning.
Background in financial services or regulated enterprise environments.
Experience supporting self-service analytics and governed data democratization.
Familiarity with data quality, metadata management, and lineage tooling.
Experience with Databricks Asset Bundles (DAB).
Microsoft Azure Data Engineer Associate certification (DP-203).
Microsoft Fabric Analytics Engineer certification.

Responsibilities

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 for BI, self-service analytics, and advanced reporting.
Define organizational standards for data ingestion, transformation, storage, and analytics consumption.
Build, optimize, and operate reliable batch and streaming pipelines using Databricks, Fabric Data Pipelines, and Azure-native services.
Implement scalable ETL/ELT frameworks with data quality, validation, and observability.
Ensure production pipelines are resilient, performant, and cost-efficient.
Design and maintain analytics-ready star, snowflake, and dimensional data models for Power BI and enterprise BI.
Develop curated, trusted datasets and semantic layers to enable consistent business metrics and reporting.
Partner with analysts, BI developers, and business stakeholders to translate analytical requirements into scalable data solutions.
Implement and manage Databricks Unity Catalog for centralized governance, lineage, access control, and auditing.
Enforce data security, role-based access, and data classification best practices across platforms.
Ensure compliance with enterprise data governance and regulatory requirements.
Design and manage data-engineering CI/CD pipelines using Azure DevOps.
Apply best practices for version control, automated testing, environment promotion, and deployment.
Monitor production data systems for high availability and operational stability.
Integrate Azure-based platforms with other cloud data technologies as needed.