Western Alliance Bank is looking to design, build, and implement critical components of their enterprise data platform to support regulatory reporting and LFI strategy, while ensuring data engineering solutions are safe, secure, compliant, and reliable.
Requirements
- 7+ years’ experience with data engineering specifically in Extract, Transform and Load (ETL) concepts and processes, enterprise data warehouse capabilities, database principles, and other related tools and technologies; preferably strong in Azure Data Factory, Azure Synapse Analytics, and/or Databricks.
- 2+ years’ experience 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.
- Advanced level experience with at least one RDBMS and query language such as T-SQL, PL/SQL, Spark SQL.
- Advanced level experience in conceptual, logical, and physical data design.
- Familiarity with data science and analytics tools such as SAS, Tableau, Power BI.
- Familiarity with multi-cloud data management and transformation platforms or tools such as Databricks, Snowflake etc.
- Additional experience with pipeline development and leveraging Azure DevOps while working on multiple projects simultaneously.
Responsibilities
- Desing, develop and deploy data engineering solutions with Azure Data Factory, Synapse Analytics, and Azure DevOps to support Western Alliance Bank's regulatory reporting and LFI strategy.
- Develop data engineering solution designs that can be handed off to data engineering teams for execution, ensuring the reuse of components wherever feasible to maximize efficiency.
- Develop ETL and data pipeline capabilities considering how data is created, transformed, stored, archived, analyzed, and shared across Western Alliance Bank and our partner systems.
- Implement Azure DevOps CI/CD pipelines for all data solutions in adherence to Western Alliance Bank technical standards.
- Apply Test Driven Development methodology to all data solutions designed, built, and implemented.
- Lead the implementation of outcomes, recommendations, and designs from Data Governance and Enterprise Architecture.
- Lead the migration of multidimensional cubes to tabular models, optimizing data architecture for enhanced analytics and performance.
Other
- Serve as a Subject Matter Expert in the Enterprise Data & Analytics domain, as well as in adjacent areas, ensuring that data engineering solutions are safe, secure, compliant, and reliable.
- Collaborate directly with data stewards, data analysts, data engineers, enterprise architects, and business stakeholders to refine requirements and shape the objectives of enterprise data solutions.
- Mentor and guide team members, fostering a culture of excellence and continuous learning.
- Collaborate with product owners and business stakeholders to gain a working understanding of business requirements and operational processes.
- May require up to 25% travel.
