
Data Engineering Lead
3 days ago
About the organization:
DMart is one of India's leading retail chains, serving millions of customers across 425+ stores and e-commerce channels throughout India. Our core objective is to offer customers good products at great value. 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.
Key Responsibilities:
- Technical Leadership: Lead architecture design for multiple enterprise data initiatives across cloud, on-premises, and hybrid platforms.
- 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.
- 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.
- Platform Expertise: Apply deep knowledge of architecture patterns and principles, performance tuning, and best practices where Snowflake is part of the solution stack.
- Schema & Data Modelling: Develop conceptual, logical, and physical data models using consistent standards, including dimensional, normalized, and denormalized structures for analytical and operational use cases.
- Best Practices & Optimization: Provide guidance on data partitioning, indexing, access controls, naming conventions, and performance optimization across multiple platforms.
- Metadata & Data Lineage: Collaborate with governance and stewardship teams to integrate metadata management, lineage mapping, and catalog tools (Snowflake Catalog or equivalents).
- Collaboration: Work closely with analysts, governance leads, engineering teams, and application architects to align models with domain requirements and enterprise architecture standards.
- Documentation: Maintain architecture blueprints and technical diagrams using tools such as or equivalent.
- Mentorship: Guide and mentor engineers, modelers, and other technical resources on architectural best practices.
Requisites:
- 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, and even
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