
Data Science Team Lead
13 hours ago
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.
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.
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.
Maintain architecture blueprints and technical diagrams using tools such as Draw.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., 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., Experience integrating data platforms with BI tools (e.g., Power BI, Tableau).
Knowledge of MDM, data mesh concepts, and even
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