Principal Data Engineer

GreenSky is seeking a Principal Data Engineer to support business intelligence and data warehouse projects. The role designs and executes software test plans, develops automated data validation and quality checks, validates BI reports and ETL processes, documents results, collaborates with stakeholders, and mentors junior engineers.

Responsibilities:

• Design, develop, and execute software test plans, strategies, and scenarios for BI and Data Warehouse projects
• Write, optimize, and automate complex SQL queries, T-SQL stored procedures, and views for Snowflake and MS-SQL Server to support both validation and development tasks
• Create and maintain automated test suites in Python and SQL for data validation and quality checks, focusing on business rule verification and report integrity
• Validate and test business intelligence reports built with SSRS, Tableau, and Sigma, ensuring data accuracy and alignment with requirements
• Develop and enhance test frameworks for ETL processes, primarily leveraging Talend, to support data movement and transformation pipeline quality
• Document test artifacts, outcomes, and recommendations, and collaborate with report developers and stakeholders to resolve discrepancies
• Participate in agile ceremonies, daily stand-ups, sprint planning, and business requirement calls, providing technical insights and updates
• Mentor junior engineers on testing strategies, SQL best practices, and BI tool utilization

Requirements:

• Bachelor's degree (U.S. or foreign equivalent) in Computer Science, Electronic Engineering, or related engineering field or related field
• Seven (7) years of experience in the job offered or in a related role
• Using SQL and T-SQL in Snowflake and MS-SQL Server environment
• Advanced knowledge of Python for scripting and automated testing
• Experience validating and testing reports in SSRS and Tableau
• Direct experience with ETL tools including Talend
• Working in agile teams and collaborating with cross-functional stakeholders
• Developing automated validation routines for report data and ensuring accurate representation of business metrics and KPIs
• Automating repetitive and complex testing processes to improve efficiency and reliability