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Netwin- Product Specialist / Principal Data Architect - Data Intelligence Platform

Posted 18 Days Ago
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In-Office
Nashik, Mahārāshtra
Expert/Leader
In-Office
Nashik, Mahārāshtra
Expert/Leader
Lead design and delivery of enterprise-scale data intelligence platforms: architect ingestion, storage, processing, governance and security; guide data engineering teams; engage enterprise clients; shape product roadmap; support pre-sales with demos and POCs; ensure production-ready, high-performance, governed systems.
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Job Title: Product Specialist / Principal Data Architect – Data Intelligence Platform

Role Overview

We are looking for a highly experienced Product Specialist / Technical Architect to lead the design, development, and delivery of our Data Intelligence Platform for large enterprise clients. This role requires a blend of deep technical expertise, product thinking, and client-facing leadership to drive scalable, enterprise-grade data solutions.

Key Responsibilities

1. Solution Architecture & Platform Design

  • Design and architect scalable, secure, and high-performance data intelligence platforms
  • Define architecture across:
    • Data ingestion (batch & real-time)
    • Data storage (data lakes, warehouses)
    • Data processing (ETL/ELT pipelines)
    • Data governance and security
  • Ensure platform supports large-scale enterprise data workloads

2. Data Engineering & Analytics Leadership

  • Guide teams in building robust pipelines for big data processing and analytics
  • Oversee implementation using modern stack (e.g., Spark, Kafka, distributed systems)
  • Drive best practices in:
    • Data modeling
    • Data quality
    • Performance optimization
  • Enable advanced analytics, BI, and AI/ML integrations

3. Enterprise Client Engagement

  • Act as primary technical advisor to enterprise clients
  • Work closely with client CTOs, data teams, and architects
  • Conduct:
    • Technical workshops
    • Solution demonstrations
    • Architecture reviews
  • Translate business requirements into scalable technical solutions

4. Product Thinking & Platform Evolution

  • Contribute to product roadmap and feature prioritization
  • Align platform capabilities with enterprise needs:
    • Data governance
    • Metadata management
    • Self-service analytics
  • Drive reusable components and accelerators

5. Team Leadership & Delivery Management

  • Lead and mentor data engineers, analysts, and developers
  • Ensure delivery of enterprise-grade, production-ready systems
  • Manage:
    • Project timelines
    • Technical risks
    • Quality standards
  • Establish development and deployment best practices

6. Pre-Sales & Capability Demonstration

  • Support sales and business teams in solutioning and proposals
  • Demonstrate platform capabilities to prospective clients
  • Create POCs, demos, and technical presentations
  • Position the company as a trusted data intelligence partner

Required Skills & Experience

Technical Expertise

  • Strong experience in:
    • Big Data technologies (Spark, Hadoop ecosystem)
    • Data Warehousing (Snowflake, Redshift, BigQuery, etc.)
    • Streaming platforms (Kafka, Flink)
  • Hands-on with:
    • Cloud platforms (AWS, Azure, GCP)
    • Data Lake / Lakehouse architectures
  • Good understanding of:
    • Data governance tools (e.g., Apache Atlas, Ranger)
    • Metadata management & lineage
    • Security & compliance

Architecture & Design

  • Experience designing enterprise-scale data platforms
  • Knowledge of:
    • Microservices architecture
    • Kubernetes / containerization
    • Distributed systems

Leadership & Client Management

  • Proven experience working with large enterprise clients
  • Strong stakeholder management and communication skills
  • Ability to manage cross-functional teams

Nice to Have

  • Experience with AI/ML integration in data platforms
  • Exposure to Agentic AI / AI-driven data workflows
  • Prior experience building or scaling a data platform product

Experience

  • 10+ years in data engineering / analytics / platform architecture
  • 3–5 years in architecture or leadership role

Experience working with enterprise-scale datasets and systems

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