Analytics Data Engineering

The Lead Solution Designer – Data & Analytics plays a pivotal leadership role within our evolving Data Engineering organization. This position is responsible for defining and driving the technical vision, architecture, and implementation of enterprise‑grade data solutions on AWS. You will lead strategic initiatives, design scalable cloud‑based data ecosystems, and ensure the performance, security, and reliability of the Data & Analytics (D&A) platform.

This role is ideal for a senior technical leader with deep AWS expertise who can balance hands‑on engineering with strategic solution design while mentoring and guiding regional data engineering teams.

Key Responsibilities:

• Lead the implementation, optimization, and delivery of data solutions using AWS core data services, driving innovation across Data Engineering, Governance, and Integration.
• Oversee all technical aspects of AWS‑based data systems, ensuring seamless end‑to‑end delivery.
• Coordinate with cross‑functional and cross‑country stakeholders to ensure timely execution and value realization.
• Continuously enhance the D&A platform to improve performance, resiliency, scalability, and security while adopting modern data technologies and methodologies.
• Translate complex business requirements into robust technical solutions in collaboration with business partners, data architects, and engineering teams.
• Design and implement enterprise data management strategies, including Data Lakehouse, Data Warehousing, Master Data Management, and Advanced Analytics solutions.
• Combine strategic solutioning with hands‑on engineering—actively contributing to architecture, coding, and deployment of critical data systems.
• Monitor system health, platform performance, and operational stability; proactively identify and resolve issues.
• Ensure data accuracy, consistency, and quality across applications, analytics, and decision‑making processes.
• Champion best practices in data engineering, governance, and AWS cloud technologies; advise on emerging tools, patterns, and standards.
• Mentor, guide, and develop data engineering teams, fostering technical excellence, collaboration, and continuous learning.

Requirements:

• 10+ years of hands‑on experience in data engineering, solution design, and enterprise data architecture with deep AWS expertise.
• Proven experience designing and implementing AWS data services (S3, Redshift, Athena, Glue, Lambda, etc.) and strong knowledge of data service design patterns.
• Expertise in building large‑scale data platforms: Data Lakehouse, Data Warehouse, MDM, and Advanced Analytics systems.
• Strong communication skills with the ability to articulate complex technical concepts to both technical and non‑technical audiences.
• Experience collaborating with multi‑disciplinary teams and aligning data strategies with business objectives.
• Demonstrated ability to manage multiple projects in fast‑paced, high‑pressure environments.
• Hands‑on proficiency in PySpark for designing, building, and optimizing large‑scale batch and streaming pipelines on AWS (essential).
• Proficiency in workflow orchestration platforms for scheduling, monitoring, and managing complex data pipelines.
• Experience optimizing cloud costs and resource utilization in large‑scale data environments.
• Strong background in CI/CD‑driven deployment and management of AWS data infrastructure.
• Expertise in Master Data Management (MDM) architectures and enterprise data governance.
• Proven experience designing and implementing Advanced Analytics solutions, including ML pipelines and statistical modeling.
• Proficiency in modern API development frameworks and API‑first data architecture patterns.
• Strong analytical and problem‑solving skills with a methodical, data‑driven approach.
• Solid understanding of data governance frameworks and best practices.
• Proficiency in data solution coding for integration, access, and analytical enablement.
• Demonstrated leadership in mentoring and developing technical teams.
• Excellent verbal and written communication skills; able to provide structure in ambiguous situations.

Good to Have

• Experience in the Insurance domain.
• AWS or relevant cloud/data architect certifications.