2746 - Data Architect – Enterprise Data Management

Title: Data Architect – Enterprise Data Management

Experience: 12+ years

Location: Delhi NCR, Bangalore, Pune (Hybrid)

Job Summary: We are seeking a seasoned Data Architect with 12+ years of experience in designing scalable, metadata-driven data architectures. This individual will lead initiatives spanning enterprise metadata management, federated query design, real-time data integration, and semantic layer modelling. The ideal candidate will be hands-on, able to translate complex requirements into robust solutions, and collaborate closely with business, technology, and governance stakeholders. Strong communication and documentation skills are essential, as this role operates at the intersection of data strategy, engineering, and enterprise governance.

Must Have Skills:

12+ years of experience in data architecture and engineering, with deep expertise in metadata-driven, federated, and real-time data environments

Core Competencies

• Enterprise Metadata Management: Design and implementation of automated data discovery, cataloguing, and lineage tracking across heterogeneous data platforms
• Federated Query Architecture: Building unified data access layers that abstract complexity across multiple data sources and query engines
• Real-time Data Integration: Event-driven architectures for continuous metadata synchronization and schema evolution management
• Data Governance Frameworks: Establishing automated data quality, privacy compliance, and access control patterns at enterprise scale
• Semantic Layer Design: Creating business-friendly data models that bridge technical schemas with analytical requirements

Technical Proficiencies

• Programming: Python (data engineering libraries), SQL (advanced optimization), Scala/Java
• Data Modelling: Dimensional modelling, graph databases, semantic web technologies
• Search & Discovery: Full-text search engines, vector similarity search, ML-based data classification
• API Architecture: REST, GraphQL, and gRPC for data service exposure
• Streaming Platforms: Message queuing and event streaming architectures
• Track record of effective collaboration with Data Engineers, Governance Leads, BI/Analytics Developers, ML Engineers, and Product Owners on complex data initiatives
• Demonstrated ability to produce data architecture diagrams, lineage flows, and maintain high-quality documentation standards
• Excellent written and verbal communication skills, with the ability to interact with executive sponsors, technology teams, and governance stakeholders
• Self-driven, hands-on architect with a lead-by-doing mindset for solution validation, issue resolution, and cross-team enablement

Nice to Have Skills:

• Implementation experience with enterprise knowledge graphs
• Understanding of data mesh and data fabric architectural approaches
• Experience with MLOps environments and integration of feature stores
• Execution of multi-cloud data strategies (e.g., AWS, Azure, GCP)
• Exposure to vector search, ML-based classification, and automated data discovery
• Familiarity with full-text search engines and search-driven metadata environments

Role & Responsibilities:

• Architect, implement, and evolve the enterprise metadata and data architecture to enable discovery, quality, and governance at scale
• Lead the design of a federated query layer that abstracts data access across distributed platforms and technologies
• Define and implement semantic layers for business-friendly data modeling and reporting enablement
• Develop and enforce data governance rules via architectural automation and controls
• Collaborate across functions with Data Engineers, Analytics Teams, Governance Stakeholders, UI/UX Designers, and ML Engineering teams to ensure architectural alignment and delivery
• Enable real-time metadata synchronization, schema tracking, and classification pipelines
• Create and maintain data architecture documentation, lineage maps, and solution artifacts
• Support strategic initiatives involving data mesh, knowledge graph, MLOps, and cloud-native data ecosystems
• Drive solutioning, reviews, and standards as a technical advisor and hands-on architect
• Communicate architectural vision, design decisions, and roadmap updates with executives, product owners, and technical teams

Key Skills: Metadata management, Data architecture, Semantic modeling, Federated queries, Real-time integration, Data governance, Python, SQL, Scala, Graph modeling, GraphQL, Kafka, API design, Data mesh, Knowledge graph