Role Overview
We are seeking an experienced Delivery Lead – Data & AI to drive end-to-end delivery of large-scale data transformation initiatives, including cloud migration and modern data platform implementations using Snowflake. This role will be responsible for leading cross-functional teams, managing client relationships, ensuring high-quality delivery, and enabling organizations to unlock value from data and AI solutions.
The ideal candidate combines strong program delivery experience, deep understanding of modern data platforms, and hands-on knowledge of cloud-based data ecosystems.
Key Responsibilities
· Lead end-to-end delivery of Data & AI transformation programs, including data platform modernization, cloud migration, and advanced analytics initiatives.
· Manage multiple data engineering and AI projects while ensuring on-time delivery, quality, and budget adherence.
· Establish delivery governance, risk management frameworks, and program reporting for leadership and clients.
Cloud & Data Platform Transformation
· Lead migration of legacy/on-prem data platforms to cloud environments such as AWS, Azure, or GCP.
· Drive design and implementation of modern data architectures using Snowflake as the central data platform.
· Ensure best practices in data ingestion, transformation, orchestration, and data governance.
Snowflake & Data Engineering Enablement
· Oversee implementation of Snowflake-based data warehouses/lakehouses.
· Guide teams on performance optimization, data modeling, cost optimization, and security within Snowflake.
· Ensure integration with modern data tools such as dbt, Airflow, Spark, Kafka, and ETL/ELT frameworks.
AI & Advanced Analytics Enablement
· Collaborate with data science and AI teams to enable scalable ML/AI pipelines on cloud data platforms.
· Support initiatives in predictive analytics, machine learning, and AI-driven insights using modern data infrastructure.
Stakeholder & Client Engagement
· Serve as the primary interface for client stakeholders, including CIO, CDO, and business leaders.
· Translate business objectives into scalable data architecture and delivery roadmaps.
· Present program status, risks, and outcomes to senior leadership.
Team Leadership
· Lead and mentor data engineers, architects, AI engineers, and analysts.
· Build strong delivery teams and ensure technical excellence and best practices.
· Foster a culture of innovation, accountability, and continuous improvement.
