AI Data Enablement Lead
Position Overview
The AI Data Enablement Lead is a senior individual contributor role responsible for the end-to-end delivery of enterprise data solutions on the Databricks Lakehouse platform. This role combines technical leadership with hands-on data engineering to ensure timely, high-quality delivery of scalable, secure, and performant data pipelines and analytics solutions.
Responsibilities
Own end-to-end delivery of data initiatives on the Databricks platform, from design through implementation and production support.
Plan and manage delivery timelines, milestones, dependencies, and risks to ensure successful outcomes.
Cook up work across onsite and offshore teams to ensure alignment, productivity, and quality delivery.
Act as the primary technical delivery point of contact for business and technology stakeholders.
Provide technical leadership and solution design guidance for Databricks-based data integration and analytics solutions.
Ensure data architecture and implementation align with enterprise standards for scalability, security, and performance.
Enforce best practices for data modeling, ETL/ELT design, analytics, and platform governance.
Design, develop, and manage data pipelines using Databricks, Apache Spark, Azure Data Factory (ADF), and SQL.
Lead ingestion, transformation, and processing of data from enterprise and regional source systems into data Lakehouse in Databricks.
Review and optimize SQL queries, Spark jobs, and ADF workflows for performance, reliability, and maintainability.
Ensure data quality, accuracy, data lineage and consistency for downstream analytics and reporting.
Monitor and troubleshoot data pipelines and platform issues to ensure stable operations.
Drive performance tuning, reliability improvements, and operational best practices.
Ensure data security, access controls, and compliance with enterprise governance standards.
Partner with business leaders, data architects, analysts, and data scientists to support analytics and decision-making needs.
Mentor and guide data engineers, promoting strong engineering discipline and delivery ownership.
Drive continuous improvement, modernization, and innovation across data delivery processes and platforms.
Commitment to The Ascot Way
Embody The Ascot Way in their daily interaction with colleagues, fostering colleague engagement and development, collaboration, inclusivity, and individual accountability.
Requirements
Bachelor’s degree in information systems, Computer Science, Data Analytics, or a related field (or equivalent experience).
Minimum of 7 years of hands-on experience delivering enterprise data solutions using Databricks.
Hands-on expertise with Databricks workspaces, unity catalogs, Apache Spark, SQL, and Azure Data Factory (ADF).
Proven experience leading technical delivery for data engineering initiatives.
Solid understanding of data integration, ETL patterns, and analytics use cases.
Experience working with cloud-based data platforms.
Strong communication, coordination, and stakeholder management skills.
Experience leading or coordinating work across distributed or offshore teams.
Prior experience as a Data Delivery Lead, Technical Lead, or Senior Data Engineer role in Insurance domain will be a plus.
Familiarity with enterprise data governance, security, and performance optimization.
Experience supporting large-scale analytics or reporting platforms.