Snowflake Senior technical lead

Ex; Gurugram District; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

Ex seeks a Senior Snowflake CoE Leader to drive architecture, delivery, and governance for large enterprise data initiatives in India. You will shape reference architectures, establish accelerators, and mentor teams across Snowflake, dbt, and the modern data stack.

You will partner with clients to define data strategies, lead workshops, and oversee delivery metrics while enabling cost optimization and secure, scalable solutions.

Qualifications

• 15+ years in data engineering/analytics/data platform roles.
• 7+ years in Snowflake with architecture and delivery experience.
• Proven leadership of CoE/practice or large delivery teams.
• Deep Snowflake knowledge: Snowpipe, Streams & Tasks, Dynamic Tables, Secure Sharing.

Responsibilities

• Lead Snowflake CoE leadership & strategy, defining reference architectures and accelerators.
• Own end-to-end Snowflake architecture for enterprise programs and governance.
• Drive delivery leadership, KPIs, FinOps, and CI/CD/DataOps/DevSecOps adoption.
• Engage clients to define data strategies, roadmaps, and transformation journeys.
• Mentor architects and engineers; build communities around Snowflake and the modern data stack.

Skills

Snowflake

Data modelling

Performance tuning

Data governance

ELT/ETL pipelines

Client-facing consulting

Cloud data engineering

Tools

ADF

Airflow

dbt

Matillion

Informatica

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)