MTS, Data Engineering (Snowflake / Finance Systems)

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.

Key Responsibilities

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

Required Skills

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)

Nice to Have

• 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