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# Data Platform Engineer

- **Company:** Banc of California
- **Location:** Durham, NC, United States
- **Experience:** Experienced
- **Salary:** $78,000.0 - $117,500.0
- **Contract:** Permanent contract
- **Skills:** Query Performance, Artificial Intelligence, Business Analytics Applications, Data Analysis, Audit Trail, Microsoft Azure, Business Intelligence Development, Cloud Computing, Cloud Engineering, Information Systems, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Data Transformation, Data Systems, DevOps, Disaster Recovery, Github, Python (Programming Language), Query Optimization, Power BI, DataOps, Azure Data Lake, SQL Databases, Enterprise Data Management, Scripting, Data Ingestion, Azure Data Factory, System Availability, Snowflake, Data Strategy, Git, Microsoft Fabric, Information Technology, Deployment Automation, Terraform, Azure Synapse Analytics, Software Version Control, Data Pipelines, Alteryx
- **Published:** September 1, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3373889543&tx=KL707PFK&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Bachelor's degree in computer science, Information Technology, Information Systems, Engineering, or a related technical discipline.
 * 3-4 years of experience in Data Engineering, Data Platform Engineering, Cloud Engineering, or a related technical role.
 * Hands-on experience with Microsoft Azure services, including Azure Data Factory (ADF), Azure Data Lake Storage Gen2 (ADLS Gen2), and Azure Synapse Analytics.
 * Experience developing and supporting data solutions on Snowflake.
 * Familiarity with dbt or similar modern data transformation frameworks.
 * Strong SQL development, query optimization, and troubleshooting skills.
 * Experience with Git, Azure DevOps, CI/CD pipelines, and source control best practices.
 * Working knowledge of Python for scripting, automation, and operational support.
 * Strong analytical, problem-solving, and communication skills with the ability to work collaboratively in a team environment.
 * Experience with Infrastructure as Code (Terraform or similar tools).
 * Exposure to DataOps, DevOps, data observability, or monitoring platforms.
 * Experience working within Banking or Financial Services.
 * Familiarity with Medallion Architecture and modern cloud data warehouse design principles.
 * Experience supporting or administering enterprise data tools such as Power BI, Microsoft Purview, Alteryx, or similar data governance, integration, and analytics platforms.
 * Microsoft Azure certifications (AZ-900, DP-203) and/or Snowflake SnowPro certification.
 * High school diploma or equivalent required.

## Description

The Data Platform Engineer will help build, operate, and continuously enhance the bank's modern cloud-based data platform. Working closely with the AVP of Platform Engineering, this role supports the enterprise data ecosystem by developing and maintaining scalable, secure, and reliable data solutions using Microsoft Azure, Snowflake, and dbt. The position will help build the data ingestion layer that lands source-system data into the Snowflake Raw layer, optimize platform performance, implement CI/CD and DataOps practices, support the broader ecosystem of enterprise data tools, and enable trusted, high-quality data for enterprise reporting, analytics, and AI initiatives.

This position offers an excellent opportunity to work with modern cloud technologies while collaborating with Data Engineering, Architecture, Business Intelligence, and business stakeholders to advance Banc of California's enterprise data strategy. The ideal candidate is passionate about cloud technologies, automation, and data engineering best practices. Performs all duties in accordance with the Company's policies and procedures, all U.S. state and federal laws and regulations, wherein the Company operates., * Support the enterprise cloud data platform built on Microsoft Azure (ADF, Synapse, ADLS), Snowflake, and dbt.

 * Help build the ingestion layer from source systems to the Snowflake Raw layer, developing and optimizing scalable batch, CDC, and streaming pipelines.
 * Support onboarding of new source systems, including connectivity, ingestion patterns, and pipeline audit logging, landing trusted data in Raw for downstream transformation by Analytics Engineering.
 * Provide reliable environments, deployment automation, and platform services that support Data Engineering's dbt transformation workloads.
 * Tune and optimize Snowflake compute, storage, and query performance to improve platform efficiency and cost management.

Operational Readiness & Automation

 * Build monitoring, alerting, and operational runbooks that enable Data Operations to monitor and manage production workloads.
 * Serve as Tier 2 escalation for pipeline failures and root cause analysis.
 * Support CI/CD deployments using Azure DevOps, GitHub, and Git-based development practices.
 * Support change management, deployment controls, and evidence requirements consistent with a SOX-controlled environment.
 * Develop automation solutions using SQL and Python to improve operational efficiency and reduce manual effort.
 * Provide Tier 2 production support and contribute to platform maintenance and continuous improvement initiatives.
 * Support platform resilience and disaster recovery initiatives, including Infrastructure as Code deployment of failover capabilities.

Enterprise Data Tools & Ecosystem Support

 * Provide platform support for enterprise data tools including Power BI, Microsoft Purview, and Alteryx, covering deployment, configuration, connectivity, and integration with the Snowflake and Azure environment.
 * Support the build-out of the Purview data governance platform, including scanning, classification, and metadata ingestion for the enterprise data catalog.
 * Help evaluate, implement, and operationalize additional data platform tools as the ecosystem expands, including data integration, self-service analytics, and other ancillary capabilities.

Collaboration & Continuous Improvement

 * Partner with Data Engineers, Data Architects, BI Developers, and business stakeholders to deliver reliable and scalable data solutions.
 * Document technical designs, operational procedures, and platform standards.
 * Identify opportunities to improve platform reliability, scalability, security, monitoring, and operational excellence.
 * Follow all established policies and procedures.
 * Perform other duties and projects as assigned.


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