About this role
Job Summary
The Snowflake Data Arch Lead is responsible for architecting and delivering enterprise-scale data solutions using Snowflake, DBT, SQL, and Python. This role provides architectural leadership, drives technical strategy, and ensures alignment with industry best practices. The position plays a critical part in enabling data-driven decision-making, fostering innovation, and establishing governance for robust, scalable, and secure data platforms.
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Section Title: Key Responsibilities
Key Responsibilities
- 1. Provide Architectural Leadership By Designing And Implementing Enterprise-Scale Data Solutions Using Snowflake, Ensuring Scalability, Performance, And Alignment With Organizational Objectives.
- 2. Define And Enforce Data Modeling Standards And Best Practices In Snowflake And Dbt, Establishing Governance And Compliance Measures Across All Project Deliverables.
- 3. Lead The Integration Of Data Pipelines Using Python And Sql, Optimizing Etl/Elt Workflows For Reliability And Efficiency.
- 4. Collaborate With Business Stakeholders To Translate Complex Requirements Into Innovative Snowflake-Based Architectures That Support Strategic Business Initiatives.
- 5. Guide and mentor technical teams in adopting advanced snowflake features, DBT transformations, and sql optimization techniques to ensure delivery excellence.
- 6. Oversee architectural reviews and ensure all solutions adhere to security, compliance, and data governance standards within the Snowflake ecosystem.
- 7. Drive continuous knowledge enhancement by evaluating emerging snowflake features and industry trends, and disseminating best practices across teams.
- 8. Contribute to organizational thought leadership by submitting whitepapers, participating in industry forums, and supporting patent filings in the data architecture domain.
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Section Title: Skill Requirements
Skill Requirements
- 1. Architectural leadership in snowflake, including advanced proficiency in data warehousing concepts, security, and scalability
- 2. InDepth Expertise In Dbt For Data Transformation And Workflow Orchestration
- 3. Advanced Proficiency In Sql For Complex Data Modeling, Query Optimization, And Analytics
- 4. Solid Experience With Python For Data Engineering And Automation Tasks
- 5. Excellent Understanding Of Data Governance, Compliance, And Security Best Practices In Cloud Data Platforms
- 6. Strong Ability To Translate Business Requirements Into Scalable Technical Solutions