Senior Enterprise Data Architect

About the organization:

• Our company is a leading retail chain, serving millions of customers across 425+ stores and e-commerce channels throughout India.

We focus on everyday low pricing, seamless shopping experiences, and data-driven decision making. As we scale our data analytics journey, we're seeking a Data Engineering Lead to drive our next phase of growth.

1. Technical Leadership: Lead architecture design for multiple enterprise data initiatives across cloud, on-premises, and hybrid platforms.
2. Data Platform Architecture and Implementation: Define and document multi-layered architectures (Raw, Curated, Analytics) across data warehouses, lake houses, and operational data stores, with an emphasis on cloud-based solutions.
3. Production Management: Directly run daily processes for efficient and reliable delivery of all programs end to end for data sync of the data lake – including oversight of change management for enrichment as per CRs.
4. Platform Expertise: Apply deep knowledge of architecture patterns and principles, performance tuning, and best practices where Snowflake is part of the solution stack.
5. Scheme & Data Modelling: Develop conceptual, logical, and physical data models using consistent standards, including dimensional, normalized, and denormalized structures for analytical and operational use cases.
6. Best Practices & Optimization: Provide guidance on data partitioning, indexing, access controls, naming conventions, and performance optimization across multiple platforms.
7. Metadata & Data Lineage: Collaborate with governance and stewardship teams to integrate metadata management, lineage mapping, and catalog tools (Snowflake Catalog or equivalents).
8. Collaboration: Work closely with analysts, governance leads, engineering teams, and application architects to align models with domain requirements and enterprise architecture standards.
9. Documentation: Maintain architecture blueprints and technical diagrams using tools such as Draw.io or equivalent.
10. Mentorship: Guide and mentor engineers, modelers, and other technical resources on architectural best practices.

• Qualifications: Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related field.
• Experience: 12+ years of IT experience with a strong background in data engineering, modeling, and architecture. 5+ years of experience designing and implementing enterprise data platforms (cloud/on-prem), including at least 3 years with Snowflake.
• Proficiency in SQL, schema design, and data modeling tools. Certifications in Snowflake incl data modelling, data extracts/ingestion will be given preference.
• Strong knowledge of ELT/ETL patterns, data integration, and orchestration tools (e.g., Airflow).
• Integration Experience with ETL and ELT tools and applications incl SAP ABAP Experience with streaming data platforms and OData. Experience with CDC patterns.
• Experience designing data layers (Raw, Curated, Analytics) with governance and scalability in mind.
• Familiarity with security and compliance frameworks, including RBAC and regulatory requirements.
• Proven track record in project delivery, including performance optimization and handling large-scale dataset.
• Experience with SAP R3 or SAP BW and Google BigQuery.
• Certifications in cloud platforms or enterprise architecture (e.g., TOGAF, DAMA, SnowPro, Azure, GCP).
• Experience integrating data platforms with BI tools (e.g., Power BI, Tableau).
• Knowledge of MDM, data mesh concepts,