Senior Data Engineering Manager - Conversational AI & Finance Control Tower

Pure Storage
Bangalore, IndiaPosted 16 April 2026

Job Description

We’re in an unbelievably exciting area of tech and are fundamentally reshaping the data storage industry. Here, you lead with innovative thinking, grow along with us, and join the smartest team in the industry. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE The Data Analytics team at Ever Pure is looking for a Senior Manager for designing and building an AI-ready data infrastructure powering conversational AI and chatbot experiences f or Finance. This role will lead the end-to-end build, defining the target state, identifying capability gaps, and delivering a phased roadmap with measurable outcomes. A core focus is enabling a conversational, AI-driven Finance experience, allowing stakeholders to access insights through natural language and copilots. WHAT YOU'LL DO Finance Control Tower Data Foundation Lead the design and build of the Finance Control Tower Establish a scalable, AI-ready data platform for reporting, analytics, and AI Deliver unified, trusted views across Finance (revenue, billing, forecasting) Data Architecture, Semantic Layer Observability Define data architecture and unified models across systems (Salesforce, SAP, NetSuite, Zuora) Build a semantic / metrics layer to standardize business definitions Implement data management and observability (quality, lineage, reliability) Conversational AI AI Enablement Enable natural language access to Finance data via chatbots and copilots Build RAG-based architectures using structured and unstructured data Develop embeddings and semantic context layers for business-aware insights Leverage platforms like Snowflake Cortex (or similar) for search, summarization, and classification Data Engineering AI Integration Build and scale data pipelines and AI-ready datasets in Snowflake (or similar) Integrate enterprise data sources (SFDC, NetSuite, Zuora) Enable LLM-driven use cases (forecasting, anomaly detection, variance analysis) Ensure outputs are accurate, explainable, and traceable We are primarily an in-office environment and therefore, you will be expected to work from the Bangalore office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave. WHAT YOU BRING 15+ years in data engineering, analytics, or related roles Experience building modern data platforms / data products at scale Strong expertise in: SQL, data modeling, ETL/ELT Semantic / metrics layer design Data governance, quality, and observability Experience with Snowflake (or similar) and Python Exposure to: Conversational AI / chatbot systems RAG, embeddings, vector search LLM frameworks and prompt design Understanding of Finance data (ARR, MRR, revenue) preferred Strong execution, stakeholder management, and communication skills #LI-ONSITE WHAT YOU CAN EXPECT FROM US: Innovation : We celebrate those who think critically, like a challenge, and aspire to be trailblazers. Growth : We give you the space and support to grow along with us and to contribute to something meaningful. We have been named Fortune's Best Workplaces in Technology™, Fortune's Best Workplaces in the Bay Area™, and certified as a Great Place to Work®! Team : We build each other up and set aside ego for the greater good. And because we understand the value of bringing your full and best self to work, we offer a variety of perks to manage a healthy balance, including flexible time off, wellness resources, and company-sponsored team events. Check out purebenefits.com for more information. ACCOMMODATIONS AND ACCESSIBILITY: Candidates with disabilities may request accommodations for all aspects of our hiring process. For more on this, contact us at TA-Ops@purestorage.com if you’re invited to an interview. OUR COMMITMENT TO A STRONG AND INCLUSIVE TEAM: We’re forging a future where everyone finds their rightful place an ... (truncated, view full listing at source)
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