Data Engineer
- United States
$115,000 to $140,000 USD / year
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Job details
- Pay
- $115,000 to $140,000 USD / year
- Experience
- 3-6 years of professional experience in data engineering, data platform development, or analytics engineering.
- Posting language
- English
- Posted
Original job description
Data Engineer Location: United States Job Type: Full-Time | Exempt | Hybrid/Remote Eligible Salary Range: $115,000 – $140,000 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 Data Engineer builds, maintains, and supports reliable, secure data pipelines and analytical data stores that power enterprise analytics, reporting, and AI use cases. With 3-6 years of hands-on data engineering experience, this role works within established architecture standards, partnering with other team members to deliver and operate solutions across the Azure ecosystem. You will contribute to implementations on Microsoft Fabric, Azure Databricks, and modern lakehouse architectures, and help support the migration of Databricks workloads to Microsoft Fabric, while working with business intelligence, analytics, AI, and business stakeholders. This role emphasizes data quality, reliability, and continuous learning. Essential Duties and Responsibilities Data Platform & Pipelines
- Develop, test, and maintain batch and streaming data pipelines using Databricks, Fabric Data Pipelines, and Azure-native services.
- Implement ETL/ELT processes that ensure data quality, accuracy, and consistency across systems.
- Build and maintain lakehouse and medallion (Bronze/Silver/Gold) data layers following team standards.
- Support Databricks-to-Fabric migration work when and where applicable, including converting notebooks and pipelines, and validating results.
- Monitor pipelines, troubleshoot failures, and help tune for performance, scalability, and cost efficiency.
- Integrate and model data from FIS core banking and H360 systems into the lakehouse for analytics and reporting.
- Support pipelines for payments data (e.g., ACH, wire, card, and real-time payments), including ingestion, reconciliation, and reporting.
- 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.
- Microsoft expertise across the data and analytics stack (Fabric, Azure Data Lake, Synapse, Power BI, Microsoft Purview).
- Plan and execute Databricks-to-Fabric migrations, including workload assessment, Delta/OneLake data movement, notebook and pipeline conversion, semantic model re-pointing, validation, and cutover where applicable.
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 developers, analysts, and business stakeholders to translate reporting requirements into scalable data solutions.
DevOps, CI/CD & Reliability
- Implement and manage CI/CD pipelines using Azure DevOps, Git for data engineering source control and automated deployments of data engineering workloads.
- Enforce best practices for source control, automated testing, deployment, and environment management.
- Ensure high availability, fault tolerance, and operational excellence for production data systems.
Governance, Security & Compliance
- Implement data governance, security, and access controls, including role-based access and data classification.
- Ensure compliance with enterprise data policies and regulatory requirements.
- Collaborate with security and infrastructure teams to enforce secure data handling and platform standards.
Data Quality Support
- Validate daily, weekly, and monthly data loads.
- Investigate data mismatches.
- Reconcile source-to-target records.
- Validate business-critical reporting datasets.
- Verify completeness, accuracy, and timeliness of data
Collaboration & Growth
- Participate in code reviews, design discussions, and team knowledge sharing.
- Communicate clearly with business, analytics, and AI teams to enable data-driven decision making.
Minimum Qualifications
- 3-6 years of professional experience in data engineering, data platform development, or analytics engineering.
- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience).
- Advanced working knowledge of SQL and hands-on experience with Python or Spark-based development.
- Hands-on experience with data pipelines and ETL/ELT concepts, including data quality checks.
- Working experience with:
- Microsoft Fabric (Lakehouse, Data Pipelines, OneLake, Semantic Models) or Azure Databricks (Spark, Delta Lake)
- Data modeling for analytics and BI
- Git and Azure DevOps (CI/CD, automated deployments)
- Business Intelligence platforms, especially Power BI
- Strong problem-solving skills and willingness to learn.
Preferred Qualifications
- FIS core banking and H360 experience, including extracting, modeling, and reconciling data from FIS core systems and H360 for analytics, reporting, and payments use cases.
- Payments experience in financial services, such as ACH, wire, card, or real-time payments data, Payment processors like TSYS, REPAY, FISERV etc; payment reconciliation and reporting; ISO 20022 and NACHA data formats.
- Databricks expertise (Unity Catalog, Delta Live Tables / Lakeflow, Databricks Workflows).
- Databricks-to-Fabric migration experience or exposure, including notebook and pipeline conversion and Power BI semantic model cutover.
- Experience in financial services, regulated industries, or enterprise environments.
- Exposure to streaming data and real-time analytics.
- Familiarity with data governance frameworks, metadata management, and data quality tooling.
- Microsoft or Databricks certifications preferred not required:
- Azure Data Engineer Associate (DP-203)
- Microsoft Fabric Analytics Engineer
- Databricks Data Engineer Associate
Benefits & Perks
- Competitive employer contribution to medical, dental and vision coverage
- 401k plan with employer match
- Flexible Spending Accounts (FSA) and Dependent Care Accounts
- Employee Assistance Program (EAP)
- Employer provided Calm subscription
- Employer provided mental health benefits through Teladoc
- Life, AD&D and disability insurance
- Minimum 15 Days of Vacation, 11 Paid Federal Holidays, Paid Time off to Volunteer
- Online discount program
- Tuition Reimbursement Program
Join Our Team!
- Submit your resume to Apply to Your Position Here
Equal Employment Opportunity & Accommodations Commercial Bank of California is proud to be an Equal Employment Opportunity employer. We are committed to creating an inclusive environment for all employees and applicants. All qualified individuals will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, protected veteran status, or any other legally protected characteristic. We evaluate applicants fairly and equitably, including those with criminal histories, in accordance with applicable federal, state, and local laws. Commercial Bank of California is also committed to providing reasonable accommodations to individuals with disabilities. If you require a reasonable accommodation during the application or interview process, please contact us at hrrecruiting@cbcal.com with the nature of your request and your contact information.
Recruitment Policy Commercial Bank of California does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to CBC, either directly or indirectly, will be considered the property of Commercial Bank of California. We will not pay a fee for any placement resulting from the receipt of an unsolicited resume. To submit candidates for consideration, recruiting agencies must have a valid, written, and fully executed agreement with Commercial Bank of California. Without such an agreement in place, no agency submissions will be accepted or compensated.
More about this job
Skills
- Reporting
- Data engineering
- Architecture regulations
- Microsoft Azure
- Databricks
- Business intelligence
- Troubleshoot
- Microsoft Power BI
- Data modelling
- Data models
- DevOps
- CI/CD
- Git
- Test automation
- Regulatory compliance
- Collaboration
- Decision making
- Computer science
- SQL
- Python
- Apache Spark
- Statistical quality control
- Problem solving
- Unity
- DP
- Google Analytics