Data Architect

Role & responsibilities

Title: Data Architect Enterprise Data Management

Experience: 12+ years

No. of Positions: 1

Location: Delhi NCR, Bangalore, Pune (Hybrid)

Job Summary:

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

o   Enterprise Metadata Management: Design and implementation of automated data discovery, cataloguing, and lineage tracking across heterogeneous data platforms

o   Federated Query Architecture: Building unified data access layers that abstract complexity across multiple data sources and query engines

o   Real-time Data Integration: Event-driven architectures for continuous metadata synchronization and schema evolution management

o   Data Governance Frameworks: Establishing automated data quality, privacy compliance, and access control patterns at enterprise scale

o   Semantic Layer Design: Creating business-friendly data models that bridge technical schemas with analytical requirements

Technical Proficiencies

o   Programming: Python (data engineering libraries), SQL (advanced optimization), Scala/Java

o   Data Modelling: Dimensional modelling, graph databases, semantic web technologies

o   Search & Discovery: Full-text search engines, vector similarity search, ML-based data classification

o   API Architecture: REST, GraphQL, and gRPC for data service exposure

o   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:

Education:

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field

• Certifications in Cloud Architecture, Metadata Management, or Data Modeling (e.g., DAMA, DCAM, TOGAF) preferred

Preferred candidate profile