THE ROLE We are seeking a highly skilled and hands-on Senior Finance Data & Analytics Engineer (IC role) to lead the design and development of the Finance Data Cube, enabling enterprise-wide insights into Customer Lifetime Value (CLTV), Contribution Margin, and other key financial metrics. WHAT YOU'LL DO Design, build, and own the Finance Data Cube, integrating financial, customer, and operational datasets. Model data to support CLTV, Contribution Margin, and other profitability KPIs across multiple dimensions (customer, product, LOB, geography, etc.) Be a data architect for Finance , bring different data into cohesive and answer critical questions Leverage AI tools to automate data summarization, anomaly detection, and narrative insights for Finance stakeholders. Scale data infrastructure to support large volumes and complex financial models. Build and manage Semantic Layer models to standardize business metrics and enable self-serve analytics Translate complex financial concepts and KPIs into scalable, maintainable data models. Implement strong controls for data quality, lineage, and governance. Maintain clear documentation of data transformations, metric definitions, and AI model logic. We are primarily an in-office environment and therefore, you will be expected to work from the Bangalore office in compliance with Pure’s policies, unless you are on PTO, or work travel, or other approved leave. WHAT YOU BRING Experience: 8+ years in Finance Data Engineering, FP&A Analytics, or Financial Systems, with exposure to AI/ML-based analytics(added advantage) Proficiency with Snowflake and modern data stacks with strong SQl and data modeling expertise Deep understanding of finance data set , SAP , Contribution margin, CLTV would be an added advantage Experience with data orchestration tools (Airflow, dbt) and tableau platform Hands-on experience with Python, PySpark, or R for automation and model integration. Proven ability to translate financial logic into scalable data models. Experience in Cortex Analyst/Search components to enable AI/ML-driven insights, natural language querying, and intelligent data discovery is preferred. Knowledge of predictive modeling, time-series forecasting, and generative AI in analytics. Ability to evaluate and apply AI responsibly in financial contexts.

About Pure Storage

Pure Storage (NYSE: PSTG) uncomplicates data storage, forever. Pure delivers a cloud experience that empowers every organization to get the most from their data while reducing the complexity and expense of managing the infrastructure behind it. Pure’s commitment to providing true storage as-a-service gives customers the agility to meet changing data needs at speed and scale, whether they are deploying traditional workloads, modern applications, containers, or more. Pure believes it can make a significant impact in reducing data center emissions worldwide through its environmental sustainability efforts, including designing products and solutions that enable customers to reduce their carbon and energy footprint. And with a certified customer satisfaction score in the top one percent of B2B companies, Pure's ever-expanding list of customers are among the happiest in the world.