Principal Engineer I - Senior Data Engineer

Join a hybrid team to build and modernize an enterprise data platform supporting the Bank Regulatory Reporting Program.

• Design, build, and implement critical components of an enterprise data platform aligned to strategic data and analytics needs for the Bank Regulatory Reporting Program
• Develop end-to-end data engineering solutions across the full data lifecycle, including efficient technical hygiene and implementation using Azure DevOps for the Bank Regulatory Reporting and LFI strategy/roadmap
• Build ETL and data pipeline capabilities covering creation, transformation, storage, archiving, analysis, and sharing across the Bank and partner systems
• Write dynamic, parameterized, and reusable PySpark code
• Create shared frameworks including helper functions and companion notebook structures
• Perform performance tuning and optimization for Spark workloads
• Implement Azure DevOps CI/CD pipelines for data solutions in accordance with Bank technical standards
• Apply Test Driven Development (TDD) to data solutions designed, built, and implemented
• Lead implementation of outcomes, recommendations, and designs from Data Governance and Enterprise Architecture
• Conduct data exploration and profiling using tools such as SSAS
• Participate in data architecture decisions
• Provide technical mentorship to team members and other data professionals
• Collaborate with product owners and business stakeholders to understand business requirements and operational processes
• Implement quality and compliance by design in all data solutions
• Include support for unstructured data and big data methods

Key skills & requirements

• 5+ years of experience (minimum)
• Expert in PySpark (required)
• 8+ years data engineering experience in ETL concepts and processes, including enterprise data warehouse capabilities and database principles; preferably strong to expert in Azure Data Factory, Azure Synapse Analytics, and/or Databricks
• 5+ years designing, implementing, and supporting cloud data solutions; Azure Data Lake, Azure Data Factory, Azure Data Services, Azure Synapse, Azure Logic Apps, and Azure DevOps experience strongly preferred
• Bachelor’s degree in engineering or related field
• Expert RDBMS and query language experience with at least one of: T-SQL, PL/SQL, Spark SQL
• Ability to design and build reusable, dynamic PySpark components including companion notebook frameworks, shared helper functions/libraries, and parameter-driven ingestion and transformation patterns
• Support and influence migration from Azure Synapse to Microsoft Fabric, including modernization of patterns and frameworks
• Expert conceptual, logical, and physical data design
• Azure certifications such as Azure Fundamentals, Azure Fabric Data Engineer, Azure Data Scientist, and/or Azure DevOps Engineer
• Experience using design tools for conceptual architecture diagrams and data flow diagrams such as Visio, Archimate, Lucidchart
• Excellent communication skills verbal and written

Tools & technologies

• PySpark, Azure DevOps, ETL
• Azure Data Factory, Azure Synapse Analytics, Databricks
• Azure Data Lake, Azure Data Services, Azure Logic Apps, Microsoft Fabric
• SSAS
• T-SQL, PL/SQL, Spark SQL
• Visio, Archimate, Lucidchart
• SAS, Tableau, PowerBI

Location & work schedule

• Phoenix, AZ (hybrid)
• 4 days on site and Fridays remote in Phoenix, AZ or Dallas, TX

Benefits

• Medical, dental, and vision coverage
• 401(k) with company match
• Short-term disability
• Life insurance with AD&D

Preferred experience

• Experience in Agile, SAFe, and/or Scrum
• Experience integrating with data quality, data catalog, and data lineage tools
• Additional cloud data certifications with major providers (Azure, AWS, GCP)
• Banking/financial services or other highly regulated industry experience
• Regulatory Reporting experience, including Large Financial Institution requirements