Snowflake Senior Technical Lead
EXL
Snowflake Senior Technical Lead
EXL
Analyzes business data and runs outsourced operations
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)
EXL analyzes business data and runs outsourced operations for insurers, healthcare payers, banks, retailers, and other large organizations. Its teams combine industry expertise with data engineering and AI to handle tasks such as claims processing, payment reviews, customer service, and finance within existing technology environments. The company also builds software, including LifePRO, which manages insurance policies, and EXLdata.ai, which connects fragmented data for use in AI systems. Clients pay for consulting projects, ongoing managed services, and software delivered through the cloud. EXL was founded in 1999 and is headquartered in New York City.
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