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Job Title:  Manager | Transformation Excellence | Bengaluru | Technology Strategy & Transformation

Manager | Data Architecture – Life Sciences| Bengaluru| 111991

 

The team

Enterprise technology has to do much more than keep the wheels turning; it is the engine that drives functional excellence and the enabler of innovation and long-term growth. Learn more about ET&P

 

Your work profile

 We are seeking a Data Architect with strong experience in designing and implementing Data Lake architecture within Life Sciences domain. The role will focus on building scalable, governed, and compliant data platforms to support advanced analytics, regulatory reporting, and digital transformation across R&D, Clinical, Regulatory, and Commercial functions.

Role: Data Architecture – Life Sciences

Location: India (Mumbai / Hyderabad / Bangalore)

Relevant experience: 5–10 years

 

Key Responsibilities

 Data Landscape Assessment & Rationalization:

•       Assess current-state data ecosystems, including data sources, pipelines, and storage platforms

•       Identify redundancies, data silos, and inefficiencies, define target-state data architecture and transformation roadmap

      Technology Evaluation:

•       Evaluate and recommend data platforms and tools (data lakes, lakehouse, ETL/ELT, streaming, cataloging, analytics) aligned to business needs

•       Conduct proof of concepts (PoCs) and vendor assessments for data technologies

     Data Architecture Design:

•       Define end-to-end Data Lake architecture (ingestion, storage, processing, semantic/consumption layers)

•       Establish scalable, reusable, and modular data architecture patterns and standards

•       Develop architecture blueprints and reference architecture for enterprise data platforms

      Data Strategy & Governance:

•       Define enterprise data strategy, including data sourcing, storage, access, and lifecycle management

•       Design and implement data governance frameworks (data quality, lineage, cataloging, master data management)

•       Establish data models, standards, and metadata management practices

      Data Integration & Interoperability:

•       Design data ingestion frameworks (batch and real-time/streaming) from diverse structured and unstructured sources

•       Enable interoperability across enterprise systems through standardized data exchange and integration patterns

•       Define data contracts and APIs for data access and sharing

     Cloud & Data Platform Modernization:

•       Drive cloud-based data lake and lakehouse implementations (AWS/Azure/GCP)

•       Modernize legacy data platforms to scalable, distributed data architectures

•       Optimize data performance, storage, and cost efficiency

    Analytics & Data Consumption Enablement:

•       Enable downstream BI, reporting, and advanced analytics/AI-ML use cases

•       Design data marts, semantic layers, and curated datasets for business consumption

     Regulatory Compliance & Data Security:

•       Ensure data platforms comply with GxP, 21 CFR Part 11, and other Life Sciences regulatory standards

•       Implement data security, privacy, and access control mechanisms

      Stakeholder Management and Collaboration:

•       Work with vendors and platform providers for implementation and optimization

•       Support client discussions, workshops, and solution presentations

     Best Practices & Capability Building:

•       Establish data engineering and architecture best practices, reusable assets, and accelerators

•       Contribute to knowledge building, documentation, and capability development within teams

 

Required Skills & Experience

 

  •         5+ years of experience in data architecture / data engineering
  • ·      Strong experience in Data Lake architecture and implementation
  • ·      Strong domain experience in Life Sciences / Pharma / Biotech
  • ·      Expertise in data modeling, ETL/ELT pipelines, and big data processing frameworks
  • ·      Hands-on experience with cloud data platforms (AWS S3, Azure Data Lake)
  • ·      Knowledge of data governance, cataloging, and lineage tools
  • ·      Familiarity with structured and unstructured data processing
  • ·      Understanding of GxP and regulatory data compliance requirements
  • Preferred Qualifications
  •         Education any graduation
  • ·      Experience with tools/platforms like Databricks, Snowflake, Azure Data Factory
  • ·      Exposure to AI/ML and advanced analytics use cases on data lakes
  • ·      Experience with data lakehouse architecture
  • ·      TOGAF / Cloud certifications (AWS/Azure)
  • Why Join Us
  • ·      Opportunity to build next-gen data platforms for Life Sciences
  • ·      Work on large-scale data transformation and analytics initiatives
  • ·      Collaborative and high-impact consulting environment

 

 

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