Assistant Vice President Snowflake Data Engineering

Exl; Dadri; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

EXL is looking for an experienced Assistant Vice President Snowflake Data Engineering to lead enterprise-scale data platforms and Snowflake modernization initiatives. You will drive architecture, delivery ownership, and mentor high-performing data teams across multiple projects.

Work with senior stakeholders to translate business requirements into scalable Snowflake solutions, optimize performance, ensure data quality and governance, and manage costs while advancing modern cloud data

Qualifications

• 8+ years of relevant experience in Data Engineering, Data Platforms, Data Warehousing, or Data & Analytics.
• Demonstrated architecture and delivery ownership on Snowflake projects.
• Strong leadership and people management experience.

Responsibilities

• Lead architecture, development, modernization, and optimization of Snowflake-based data platforms.
• Define Snowflake data architecture, engineering standards, and best practices.
• Oversee data ingestion, ETL/ELT, data transformation, modelling, and data products.

Skills

Snowflake

SQL

Python/PySpark

Data architecture

ETL/ELT

Data modelling

Cloud platforms (AWS/Azure/GCP)

Data governance

Airflow

Education

Bachelor's or Master's in CS/Engineering/IT/Data Science

Tools

dbt

Airflow

Informatica

Matillion

Azure Data Factory

Snowflake Streams/Tasks

Job description

Role Overview

EXL is looking for an experienced Assistant Vice President Snowflake Data Engineering to lead enterprise-scale data engineering and Snowflake modernization initiatives.

Key Responsibilities

• Lead the architecture, development, modernization, and optimization of enterprise-scale data platforms built on Snowflake.
• Define Snowflake data architecture, engineering standards, development frameworks, and best practices.
• Lead teams responsible for data ingestion, ETL/ELT, data transformation, data modelling, data integration, and data products.
• Design scalable Snowflake solutions for high-volume, complex, and business-critical workloads.
• Drive migration and modernization of legacy data warehouses and platforms to Snowflake.
• Own delivery across multiple projects/programs, including scope, timelines, quality, SLAs, risks, and resource planning.
• Build, mentor, and manage high-performing data engineering teams.
• Partner with senior business and technology stakeholders to translate business requirements into scalable data solutions.
• Drive Snowflake performance optimization, workload management, scalability, and cost optimization.
• Establish strong practices around data quality, governance, security, lineage, monitoring, and operational excellence.
• Drive automation across data engineering development, testing, deployment, monitoring, and support.
• Evaluate and implement Snowflake capabilities and emerging data technologies to improve platform capabilities.
• Contribute to solutioning, proposals, client presentations, and business development initiatives where required.

Required Technical Skills

• Strong hands-on experience with Snowflake and modern cloud data platforms.
• Strong proficiency in SQL and data transformation.
• Strong experience with Python and/or PySpark.
• Deep understanding of Snowflake architecture, including warehouses, databases, schemas, stages, storage, compute, and workload management.
• Strong experience with Snowflake ELT/ETL patterns and data pipeline development.
• Strong understanding of Snowflake performance tuning and cost optimization.
• Experience with Snowflake Streams, Tasks, Dynamic Tables, Snowpipe, and Snowflake security.
• Strong understanding of data modelling, including dimensional modelling, fact/dimension structures, SCD, data marts, and enterprise data warehouses.
• Experience integrating Snowflake with cloud platforms such as AWS, Azure, or GCP.
• Experience with orchestration and integration tools such as Airflow, Azure Data Factory, dbt, Informatica, Matillion, or equivalent.
• Understanding of CI/CD, Git, DevOps, automated testing, monitoring, and production support.
• Experience with data governance, data quality, metadata, data lineage, access control, and data security.
• Knowledge of Kafka or other streaming technologies is desirable.

Leadership & Business Skills

• Demonstrated experience leading data engineering teams and multiple delivery streams.
• Strong people-management experience, including hiring, mentoring, performance management, and career development.
• Ability to communicate complex Snowflake and data architecture concepts to senior business and technology stakeholders.
• Strong program and delivery management capabilities.
• Ability to make architectural decisions considering scalability, performance, reliability, security, and cost.
• Strong stakeholder and client-management skills.
• Experience in solutioning, pre-sales, proposals, or account growth is an advantage.
• Ability to balance technical depth with strategic thinking and business outcomes.

Preferred Experience

• Experience leading Snowflake implementation or large-scale migration programs.
• Experience migrating platforms such as Teradata, Oracle, SQL Server, Hadoop, or other legacy data warehouses to Snowflake.
• Experience with Snowflake Data Cloud / modern cloud data architecture.
• Experience with dbt and modern ELT frameworks.
• Experience implementing enterprise data platforms, data marts, or data products.
• Exposure to Generative AI, ML platforms, MLOps, or AI/ML data pipelines.
• Experience in consulting, analytics, BFSI, or other complex enterprise environments.

Experience & Education

• 8+ years of relevant experience in Data Engineering, Data Platforms, Data Warehousing, or Data & Analytics.
• Strong hands-on Snowflake experience with demonstrated architecture and delivery ownership.
• Demonstrated progression into technical leadership and people management.
• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, Data Science, or a related discipline.