Snowflake COE Lead

Key Responsibilities 1. COE Leadership & Strategy

• Build and scale Snowflake CoE capabilities (architecture, engineering, governance, FinOps).
• Define reference architectures, reusable assets, frameworks, and accelerators.
• Drive capability development, hiring strategy, and upskilling initiatives.
• Establish standards for delivery quality, security, and performance. 2. Solution Architecture & Advisory
• Own end-to-end Snowflake architecture for enterprise-scale programs.
• Translate business goals into data platform strategies (lakehouse / data warehouse / modern data stack).

Design solutions across

o Data ingestion, transformation, and orchestration o Data modelling (Dimensional, Data Vault, Medallion/Lakehouse architectures) o Data consumption (BI, APIs, AI/ML integration)

• Lead architecture governance and design reviews. 3. Delivery Leadership & Governance
• Lead large-scale implementations and transformations on Snowflake.
• Define and track delivery KPIs, cost optimisation (FinOps), and performance metrics.
• Ensure adoption of CI/CD, DataOps, and DevSecOps practices.
• Act as escalation point for complex technical challenges. 4. Client Engagement & Consulting
• Partner with clients to define data strategies, roadmaps, and transformation journeys.
• Lead solution workshops, proposals, and executive discussions.
• Provide thought leadership in Snowflake, Data Engineering, and Analytics.
• Drive account growth through cross-selling and innovation-led proposals. 5. Engineering Excellence & Mentorship
• Mentor architects and engineers across projects.

Build strong internal communities around

o Snowflake o dbt / modern data stack o Cloud-native data engineering

• Promote best practices in coding, modelling, and governance. Must Have Skills & Experience
• 15+ years overall experience in data engineering / analytics / data platform roles.
• 7+ years in Snowflake with strong architecture + delivery experience.
• Proven experience in leading CoE / practice / large delivery teams.

Deep expertise in

o Snowflake (Snowpipe, Streams & Tasks, Dynamic Tables, Secure Sharing) o Data modelling (Dimensional / Data Vault / Lakehouse) o Performance tuning & cost optimisation strategies o Data governance & security (RBAC, masking, row/column security)

• Strong experience in ELT/ETL pipelines and orchestration tools (ADF, Airflow, dbt, Matillion, Informatica)
• Hands-on experience in client-facing consulting roles and solution design. Good to Have
• Experience on Azure / AWS / GCP ecosystems
• Exposure to GenAI / AI integration with data platforms
• Experience in domain analytics (Insurance, BFSI, Healthcare)
• Familiarity with modern data stack tools (dbt, Python frameworks, Spark)

Key Responsibilities 1. COE Leadership & Strategy

• Build and scale Snowflake CoE capabilities (architecture, engineering, governance, FinOps).
• Define reference architectures, reusable assets, frameworks, and accelerators.
• Drive capability development, hiring strategy, and upskilling initiatives.
• Establish standards for delivery quality, security, and performance. 2. Solution Architecture & Advisory
• Own end-to-end Snowflake architecture for enterprise-scale programs.
• Translate business goals into data platform strategies (lakehouse / data warehouse / modern data stack).

Design solutions across

o Data ingestion, transformation, and orchestration o Data modelling (Dimensional, Data Vault, Medallion/Lakehouse architectures) o Data consumption (BI, APIs, AI/ML integration)

• Lead architecture governance and design reviews. 3. Delivery Leadership & Governance
• Lead large-scale implementations and transformations on Snowflake.
• Define and track delivery KPIs, cost optimisation (FinOps), and performance metrics.
• Ensure adoption of CI/CD, DataOps, and DevSecOps practices.
• Act as escalation point for complex technical challenges. 4. Client Engagement & Consulting
• Partner with clients to define data strategies, roadmaps, and transformation journeys.
• Lead solution workshops, proposals, and executive discussions.
• Provide thought leadership in Snowflake, Data Engineering, and Analytics.
• Drive account growth through cross-selling and innovation-led proposals. 5. Engineering Excellence & Mentorship
• Mentor architects and engineers across projects.

Build strong internal communities around

o Snowflake o dbt / modern data stack o Cloud-native data engineering

• Promote best practices in coding, modelling, and governance. Must Have Skills & Experience
• 15+ years overall experience in data engineering / analytics / data platform roles.
• 7+ years in Snowflake with strong architecture + delivery experience.
• Proven experience in leading CoE / practice / large delivery teams.

Deep expertise in

o Snowflake (Snowpipe, Streams & Tasks, Dynamic Tables, Secure Sharing) o Data modelling (Dimensional / Data Vault / Lakehouse) o Performance tuning & cost optimisation strategies o Data governance & security (RBAC, masking, row/column security)

• Strong experience in ELT/ETL pipelines and orchestration tools (ADF, Airflow, dbt, Matillion, Informatica)
• Hands-on experience in client-facing consulting roles and solution design. Good to Have
• Experience on Azure / AWS / GCP ecosystems
• Exposure to GenAI / AI integration with data platforms
• Experience in domain analytics (Insurance, BFSI, Healthcare)
• Familiarity with modern data stack tools (dbt, Python frameworks, Spark)

Key Responsibilities 1. COE Leadership & Strategy

• Build and scale Snowflake CoE capabilities (architecture, engineering, governance, FinOps).
• Define reference architectures, reusable assets, frameworks, and accelerators.
• Drive capability development, hiring strategy, and upskilling initiatives.
• Establish standards for delivery quality, security, and performance. 2. Solution Architecture & Advisory
• Own end-to-end Snowflake architecture for enterprise-scale programs.
• Translate business goals into data platform strategies (lakehouse / data warehouse / modern data stack).

Design solutions across

o Data ingestion, transformation, and orchestration o Data modelling (Dimensional, Data Vault, Medallion/Lakehouse architectures) o Data consumption (BI, APIs, AI/ML integration)

• Lead architecture governance and design reviews. 3. Delivery Leadership & Governance
• Lead large-scale implementations and transformations on Snowflake.
• Define and track delivery KPIs, cost optimisation (FinOps), and performance metrics.
• Ensure adoption of CI/CD, DataOps, and DevSecOps practices.
• Act as escalation point for complex technical challenges. 4. Client Engagement & Consulting
• Partner with clients to define data strategies, roadmaps, and transformation journeys.
• Lead solution workshops, proposals, and executive discussions.
• Provide thought leadership in Snowflake, Data Engineering, and Analytics.
• Drive account growth through cross-selling and innovation-led proposals. 5. Engineering Excellence & Mentorship
• Mentor architects and engineers across projects.

Build strong internal communities around

o Snowflake o dbt / modern data stack o Cloud-native data engineering

• Promote best practices in coding, modelling, and governance. Must Have Skills & Experience
• 15+ years overall experience in data engineering / analytics / data platform roles.
• 7+ years in Snowflake with strong architecture + delivery experience.
• Proven experience in leading CoE / practice / large delivery teams.

Deep expertise in

o Snowflake (Snowpipe, Streams & Tasks, Dynamic Tables, Secure Sharing) o Data modelling (Dimensional / Data Vault / Lakehouse) o Performance tuning & cost optimisation strategies o Data governance & security (RBAC, masking, row/column security)

• Strong experience in ELT/ETL pipelines and orchestration tools (ADF, Airflow, dbt, Matillion, Informatica)
• Hands-on experience in client-facing consulting roles and solution design. Good to Have
• Experience on Azure / AWS / GCP ecosystems
• Exposure to GenAI / AI integration with data platforms
• Experience in domain analytics (Insurance, BFSI, Healthcare)
• Familiarity with modern data stack tools (dbt, Python frameworks, Spark)