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Senior Data Engineering Manager - Conversational AI & Finance Control Tower

Pure StorageBangalore, India
On-site Full-time

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Experience Level

Senior Level Manager

Qualifications

Qualifications:Proven experience in data engineering, AI integration, and data architectureStrong understanding of finance processes and data analyticsFamiliarity with tools such as Snowflake, Salesforce, SAP, NetSuite, and ZuoraExcellent communication and leadership skillsAbility to work collaboratively in a fast-paced environment

About the job

Location: Bangalore, India

Role Overview

Pine Storage’s Data & Analytics team is looking for a Senior Data Engineering Manager to lead the development of an AI-ready data infrastructure supporting conversational AI and chatbot experiences for Finance. This position covers the full project lifecycle: from defining the vision and identifying capability gaps to delivering a phased roadmap with clear, measurable results. The main goal is to create an AI-driven Finance experience where stakeholders can access insights using natural language and copilots.

Key Responsibilities

Finance Control Tower & Data Foundation

  • Design and implement the Finance Control Tower.
  • Build a scalable, AI-ready data platform for reporting, analytics, and AI integration.
  • Deliver unified and reliable views across Finance, including revenue, billing, and forecasting.

Data Architecture, Semantic Layer & Observability

  • Define data architecture and unified models across systems such as Salesforce, SAP, NetSuite, and Zuora.
  • Develop a semantic or metrics layer to standardize business definitions.
  • Implement data management and observability practices with a focus on quality, lineage, and reliability.

Conversational AI & AI Enablement

  • Enable natural language access to Finance data through chatbots and copilots.
  • Design RAG-based architectures using both structured and unstructured data.
  • Create embeddings and semantic context layers for business-aware insights.
  • Apply platforms like Snowflake Cortex for improved search, summarization, and classification.

Data Engineering & AI Integration

  • Build and scale data pipelines and AI-ready datasets within Snowflake or similar environments.
  • Integrate enterprise data sources, including SFDC, NetSuite, and Zuora.
  • Support LLM-driven use cases such as forecasting, anomaly detection, and variance analysis.
  • Ensure results are accurate, explainable, and traceable.

About Pure Storage

At Pure Storage, we are at the cutting edge of technology, redefining the data storage sector with innovative solutions. Join an environment that fosters creativity and growth, where you can collaborate with industry leaders and drive impactful change.

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