Solution Architect

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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. LONGDESCRIPTION section. 3 of 6.

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