Enterprise Data Architect

Location

Experience

Architecture Ownership

• **Own and govern the end-to-end Data Lakehouse architecture, ensuring consistency across data ingestion, storage, processing, consumption, and governance layers.**
• **Define and validate the target state Medallion Architecture (Bronze, Silver, Gold) in alignment with enterprise architecture principles.**
• **Ensure robust architectural patterns for batch, near real-time, and historical data processing.**

Platform & Technology Alignment

• **Ensure architectural consistency and seamless integration across:**
• **Cloudera Data Platform**
• **Teradata Enterprise Data Warehouse**
• **Informatica (ETL, Data Quality, Metadata)**
• **Denodo (Data Virtualization & Consumption)**
• **Review and approve low-level designs, data flows, and integration patterns across platforms.**

Phase 1 Remediation Governance

• **Perform architectural assessment and validation of Phase 1 deliverables, including:**
• **Data pipelines**
• **Logical and physical data models**
• **Gold layer aggregations (Teradata)**
• **Identify architectural gaps, anti-patterns, and misalignments.**
• **Define remediation and rebuild strategies aligned with target architecture.**

Enterprise Data Modeling & Standards

• **Govern the implementation of logical and physical data models aligned to:**
• **FSLDM (Financial Services Logical Data Model)**
• **FSAS aggregation standards**
• **Ensure correctness, consistency, and reusability of enterprise and subject-area models.**
• **Validate aggregation logic, hierarchies, and reporting readiness.**

Governance, Compliance & Security

• **Ensure alignment with:**
• **NDMO (National Data Management Office)**
• **NDI (National Data Index)**
• **data classification, privacy, and security standards**
• **Oversee metadata, lineage, data quality, and auditability design.**
• **Ensure architecture supports regulatory reporting, traceability, and reconciliation requirements.**

Performance, Scalability & Resilience

• **Define architecture patterns for:**
• **High availability (≥99.9% uptime)**
• **Horizontal scalability**
• **Disaster recovery and point-in-time restore**
• **Review and guide performance tuning strategies for ingestion, transformation, and reporting workloads.**

Stakeholder & Governance Engagement

• **Act as the primary architectural interface with IT, Data Governance, Security, and Business teams.**
• **Participate in architecture review boards, design walkthroughs, and governance forums.**
• **Clearly articulate architectural decisions, trade-offs, and impacts to senior stakeholders.**

Technical Expertise

• **Strong experience in Enterprise Data Architecture, including:**
• **EDW modernisation**
• **Data Lake / Lakehouse architectures**
• **Medallion architecture patterns**
• **Deep understanding of BFSI data domains and enterprise reference models:**
• **FSLDM**
• **FSAS**
• **Hands-on architectural exposure to:**
• **Cloudera CDP (HDFS, Spark, Hive, Kafka)**
• **Teradata Vantage**
• **Informatica (ETL)- BDM**
• **Informatica Power Exchange (CDC)**
• **Kafka**
• **Denodo**

Governance & Compliance

• **Proven experience designing governance-driven architecture:**
• **Metadata and lineage**
• **Data quality frameworks**
• **Security, masking, and encryption**
• **Strong understanding of regulatory and compliance-driven data platforms.**

Non-Functional Design

• **Expertise in:**
• **Performance and workload optimization**
• **Scalability and capacity planning**
• **Resilience, backup, and recovery design**

Soft Skills

• **Strong communication and stakeholder management skills.**
• **Ability to lead cross-vendor and cross-functional technical discussions.**
• **Governance mindset with pragmatic delivery orientation.**

Experience & Qualifications

• **15+ years of experience in data architecture roles, preferably in large BFSI organizations.**
• **Proven track record of large-scale data platform transformation programs.**
• **Experience working in hybrid delivery models with onsite and offshore teams.**
• **Architecture certification(s) or advanced data engineering background preferred..**