Job Description: 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:
- Data ingestion, transformation, and orchestration
- Data modelling (Dimensional, Data Vault, Medallion/Lakehouse architectures)
- 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:
- Snowflake
- dbt / modern data stack
- 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:
- Snowflake (Snowpipe, Streams & Tasks, Dynamic Tables, Secure Sharing)
- Data modelling (Dimensional / Data Vault / Lakehouse)
- Performance tuning & cost optimisation strategies
- 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)
Responsibilities: 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:
- Data ingestion, transformation, and orchestration
- Data modelling (Dimensional, Data Vault, Medallion/Lakehouse architectures)
- 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:
- Snowflake
- dbt / modern data stack
- 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:
- Snowflake (Snowpipe, Streams & Tasks, Dynamic Tables, Secure Sharing)
- Data modelling (Dimensional / Data Vault / Lakehouse)
- Performance tuning & cost optimisation strategies
- 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)
Qualifications: 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:
- Data ingestion, transformation, and orchestration
- Data modelling (Dimensional, Data Vault, Medallion/Lakehouse architectures)
- 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:
- Snowflake
- dbt / modern data stack
- 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:
- Snowflake (Snowpipe, Streams & Tasks, Dynamic Tables, Secure Sharing)
- Data modelling (Dimensional / Data Vault / Lakehouse)
- Performance tuning & cost optimisation strategies
- 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)
