EY - GDS Consulting - AI And DATA - Databricks - Manager

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Job Description – Data Engineering Lead (Manager)

Job Summary

We are seeking a Data Engineering Lead (Manager) to architect and drive enterprise data transformation programs for a leading Insurance client. This role will lead the design and implementation of scalable data platforms using Azure and Databricks, enabling advanced analytics, regulatory compliance, and business insights. The candidate will play a pivotal role in shaping data strategy, driving innovation, and delivering high-impact solutions in a complex enterprise environment.

Key Responsibilities

• Lead architecture and implementation of enterprise-scale data platforms using Azure and Databricks


• Define data strategy, architecture, and roadmap aligned with business and regulatory requirements


• Drive design of scalable data models, pipelines, and lakehouse architectures


• Oversee migration and modernization of legacy systems (DB2, Datastage) to cloud platforms


• Collaborate with business leaders, architects, and cross-functional teams to deliver data-driven solutions


• Implement governance, security, and compliance frameworks aligned to insurance standards


• Lead, mentor, and manage data engineering teams, ensuring best practices and delivery excellence


• Drive productivity improvements through adoption of AI/GenAI and Agentic AI-based solutions

Required Skills

• Strong experience in architecting data platforms on Azure (ADF, ADLS, Synapse) and Databricks


• Expertise in Python, SQL, Spark, and large-scale distributed data processing


• Deep knowledge of data architecture, data warehousing, and lakehouse patterns


• Experience in Insurance or BFSI domain with strong understanding of regulatory data needs


• Proven leadership experience managing teams and delivering large-scale programs


• Knowledge of DevOps, CI/CD, and modern engineering practices


• Strong stakeholder management, communication, and problem-solving skills


• Experience driving innovation through AI, automation, and data engineering accelerators

Preferred Qualifications

• Experience with Mulesoft, Datastage, and DB2 integration and migration


• Understanding of insurance domains (claims, underwriting, policy, finance)


• Microsoft Certified: Azure Data Engineer Associate (DP-203) or Azure Solutions Architect Expert


• Databricks Certified Data Engineer (Associate/Professional) or Databricks Architect certifications


• Exposure to AI/ML platforms and Agentic AI frameworks for engineering productivity improvements

Experience & Education

• 10–17 years of experience in Data Engineering, including architecture and leadership roles


• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field

Work Location

• Bangalore or Kochi

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