MTS, Data Engineering (Snowflake / Finance Systems)

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Job Category
Software Engineering

Job Details

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Member of Technical Staff (MTS) - Data Engineering (Snowflake / Finance Systems)
Role Description

• Digital Enterprise Technology (DET) is seeking a Member of Technical Staff (MTS) to join our IT Finance and Data Engineering team. This role is primarily focused on designing, developing, and optimizing solutions on the Snowflake data platform to support enterprise finance and revenue processes.
• The ideal candidate brings deep expertise in Snowflake architecture, data modeling, and data pipeline development, along with experience working with finance or revenue systems. This role will play a key part in building scalable, high-performance data solutions that enable reporting, reconciliation, and analytics across business-critical systems.

• Design, develop, and optimize Snowflake-based data solutions with a focus on scalability, performance, and governance
• Build and maintain data pipelines (ELT/ETL), transformations, and data models to support finance and operational reporting
• Develop and manage Snowflake objects including tables, views, streams, tasks, and stored procedures
• Implement performance tuning and cost optimization strategies (clustering, partitioning, query optimization)
• Partner with Finance, Data Engineering, and business teams to translate requirements into scalable data solutions
• Support data reconciliation, validation, and audit processes to ensure data accuracy and integrity
• Build and maintain integrations with upstream and downstream systems using APIs and data ingestion frameworks
• Troubleshoot and resolve data and performance issues across pipelines and datasets
• Contribute to data governance, security (RBAC), and compliance frameworks
• Participate in design reviews, testing, and deployment processes following engineering best practices

• 5-7 years of experience in data engineering or finance systems engineering
• Strong hands-on expertise in Snowflake including:
  
  
  • Data modeling and warehousing concepts
  • Performance tuning (clustering, micro-partitions, query optimization)
  • Streams, Tasks, and stored procedures
  • Security model (RBAC, data sharing)
• Advanced proficiency in SQL and data transformation techniques
• Experience building scalable ELT/ETL pipelines and handling large data volumes
• Familiarity with data orchestration tools (e.g., Airflow, dbt, Informatica, or similar)
• Experience integrating data from enterprise systems using APIs or batch ingestion frameworks
• Understanding of finance data concepts (e.g., revenue, GL, reconciliation) is a plus
• Strong analytical, troubleshooting, and problem-solving skills
• Experience working in Agile environments with CI/CD and version control (Git)

• Exposure to finance or revenue systems (e.g., Zuora Revenue or similar)
• Experience with BI/reporting tools (Tableau, Power BI, etc.)
• Familiarity with cloud platforms (AWS, Azure)
• Experience with data quality frameworks and automation