Staff Engineer II - Senior Data Engineer

Western Alliance Bank invites a Staff Engineer II - Senior Data Engineer to shape the enterprise data platform with emphasis on safety, security, compliance, and reliability. You will lead a centralized data engineering team and partner with data stewards, analysts, engineers, enterprise architects, and business stakeholders to deliver scalable data capabilities.

What you gain in this role includes:

• Competitive salaries
• Ownership stake in the company
• Medical and dental insurance
• Time off
• Great 401k matching program
• Tuition assistance program
• Employee volunteer program
• Wellness program

Location: Phoenix, AZ on-site (Block 23)

Responsibilities

• Design, develop and deploy data engineering solutions using Azure Data Factory, Azure Synapse Analytics, and Azure DevOps to support regulatory reporting and the LFI strategy.
• Create reusable data engineering solution designs ready for hand‑off to execution teams, maximizing efficiency by component reuse.
• Build ETL and data pipeline capabilities that account for data creation, transformation, storage, archiving, analysis, and sharing across Western Alliance Bank and partner systems.
• Implement Azure DevOps CI/CD pipelines for all data solutions in alignment with technical standards.
• Apply Test Driven Development to all designed, built, and implemented data solutions.
• Lead the implementation of outcomes and designs from Data Governance and Enterprise Architecture.
• Oversee migration of multidimensional cubes to tabular models to optimize analytics and performance.
• Use Power BI to design, deploy, and visualize tabular cubes for seamless business intelligence.
• Conduct data exploration and profiling with tools such as Excel and Informatica.
• Actively participate in data architecture decision making.
• Provide technical mentorship to team members and other data professionals.
• Collaborate with product owners and business stakeholders to understand requirements and operational processes.
• Embed built-in quality and compliance-by-design in all data solutions.
• Review Azure Data Factory pipelines, Synapse artifacts, and other scripts to ensure deliverables meet quality standards.

Requirements

• Bachelor’s degree in engineering or a related field; Master’s or MBA preferred.
• 7+ years of data engineering experience covering ETL concepts, enterprise data warehouses, database principles, and related tools; strong preference for Azure Data Factory, Azure Synapse Analytics, and/or Databricks.
• 2+ years designing, implementing, and supporting cloud data solutions with Azure Data Lake, Azure Data Factory, Azure Data Services, Azure Synapse, Azure Logic Apps, and Azure DevOps experience preferred.
• Advanced experience with at least one RDBMS and query language (T-SQL, PL/SQL, Spark SQL).
• Advanced data modeling skills across conceptual, logical, and physical layers.
• Azure certifications such as Fundamentals, Data Engineer, Data Scientist, and/or DevOps Engineer preferred.
• Familiarity with data science and analytics tools (SAS, Tableau, Power BI).
• Experience with multi-cloud data management and transformation platforms or tools (e.g., Databricks, Snowflake).
• Experience in Agile, SAFe, and/or Scrum frameworks preferred.
• Experience integrating with data quality, data catalog, and data lineage tools preferred.
• Previous leadership experience preferred.
• Knowledge of financial services or banking environments preferred.
• Strong understanding of regulatory and legal compliance obligations, industry standards, and practices.
• Proven ability to lead cross-functional teams and manage multiple projects concurrently, including pipeline development with Azure DevOps.
• Strategic thinker with the ability to align projects with organizational goals, motivate teams, and manage risks.
• Excellent written and verbal communication skills.
• Up to 25% travel may be required.

Technologies we work with

• Azure Data Factory
• Azure Synapse Analytics
• Azure DevOps
• Azure Data Lake
• Azure Logic Apps
• Power BI
• Excel
• Informatica
• Databricks
• Snowflake
• SAS
• Tableau
• Azure Data Services
• T-SQL
• PL/SQL
• Spark SQL