Manager Data Architecture Life Sciences Bengaluru 111991
The team
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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: 510 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 workplace