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Overview
Mid-Level

MTS, Data Engineering (Snowflake / Finance Systems)

Confirmed live in the last 24 hours

Salesforce

Salesforce

India - Hyderabad
On-site
Posted March 31, 2026

Job Description

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Job Category

Software Engineering

Job Details

About Salesforce

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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.

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 you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.

Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.

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