MTS, Data Engineering (Snowflake / Finance Systems)

Salesforce
India - HyderabadPosted 31 March 2026

Job Description

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Software Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. 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 Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so ... (truncated, view full listing at source)
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