Senior Data Engineer

Milliman Ireland; Gurugram District; On-site; INR 1,400,000 - 2,200,000; Full time

Job summary

Milliman Ireland seeks a Data Architect to lead the design and implementation of data architecture in a Microsoft Fabric-based sandbox. You will define ingestion patterns, Lakehouse structure, data layers, data quality controls, and analytics-ready datasets to support pricing, underwriting, claims, fraud, and risk segmentation analysis.

You will drive technical design for ingestion pipelines, schema handling, and incremental loading while mentoring junior engineers and coordinating with product

Qualifications

• Strong experience designing and implementing scalable data engineering or data architecture solutions.
• Hands-on experience with Microsoft Fabric, Azure data services, Lakehouse architecture, OneLake, pipelines, notebooks, and modern cloud data platforms.
• Strong understanding of bronze, silver, and gold data layer design, data modeling, data integration, and data quality frameworks.
• Proficiency in SQL, Python, Spark, and data pipeline development.
• Experience with schema management, incremental processing, partitioning, validation, reconciliation, and performance optimization.
• Ability to translate business and actuarial requirements into robust technical data models and feature datasets.
• Strong communication skills with the ability to explain technical concepts to actuarial, product, engineering, and security stakeholders.

Responsibilities

• Lead the end-to-end data architecture for the sandbox, including ingestion patterns, Microsoft Fabric Lakehouse structure, bronze, silver, and gold table strategy, and data quality framework.
• Own the technical design and implementation approach for data ingestion into Microsoft Fabric, including pipeline design, file validation, schema handling, partitioning, and incremental load strategy.
• Translate raw and curated source data into analytics-ready datasets, including daily summary, event-summary, exposure, behavioral, and contextual feature tables.
• Define and implement data profiling, reconciliation, and validation outputs such as row counts, file counts, duplicate checks, null analysis, timestamp coverage, identifier stability, and unit validation.
• Partner closely with actuarial teams to understand required features and ensure the data model supports pricing, underwriting, claims, fraud, and risk segmentation analysis.
• Provide technical direction, design guidance, and code review for junior engineers.
• Coordinate with product leadership and IT/security stakeholders on Microsoft Fabric configuration, Lakehouse setup, roadmap decisions, access controls, and environment readiness.
• Establish documentation standards for data models, transformation logic, quality rules, assumptions, limitations, and operational procedures.

Skills

Data architecture design

SQL

Python

Spark

Microsoft Fabric

Azure data services

Lakehouse

Data quality frameworks

Data modeling

Data pipelines

Schema management

Incremental processing

Communication skills

Tools

Microsoft Fabric

OneLake

Azure data services

Job description

Role Summary

The Data Architect will lead the design and implementation of data architecture for a Microsoft Fabric-based sandbox environment supporting data and actuarial discovery use cases. This role will define ingestion patterns, Lakehouse structure, data layer strategy, data quality controls, and analytics-ready datasets that enable pricing, underwriting, claims, fraud, and risk segmentation analysis.

Key Responsibilities

• Lead the end-to-end data architecture for the sandbox, including ingestion patterns, Microsoft Fabric Lakehouse structure, bronze, silver, and gold table strategy, and data quality framework.
• Own the technical design and implementation approach for data ingestion into Microsoft Fabric, including pipeline design, file validation, schema handling, partitioning, and incremental load strategy.
• Translate raw and curated source data into analytics-ready datasets, including daily summary, event-summary, exposure, behavioral, and contextual feature tables.
• Define and implement data profiling, reconciliation, and validation outputs such as row counts, file counts, duplicate checks, null analysis, timestamp coverage, identifier stability, and unit validation.
• Partner closely with actuarial teams to understand required features and ensure the data model supports pricing, underwriting, claims, fraud, and risk segmentation analysis.
• Provide technical direction, design guidance, and code review for junior engineers.
• Coordinate with product leadership and IT/security stakeholders on Microsoft Fabric configuration, Lakehouse setup, roadmap decisions, access controls, and environment readiness.
• Establish documentation standards for data models, transformation logic, quality rules, assumptions, limitations, and operational procedures.

Required Skills and Experience

• Strong experience designing and implementing scalable data engineering or data architecture solutions.
• Hands-on experience with Microsoft Fabric, Azure data services, Lakehouse architecture, OneLake, pipelines, notebooks, and modern cloud data platforms.
• Strong understanding of bronze, silver, and gold data layer design, data modeling, data integration, and data quality frameworks.
• Proficiency in SQL, Python, Spark, and data pipeline development.
• Experience with schema management, incremental processing, partitioning, validation, reconciliation, and performance optimization.
• Ability to translate business and actuarial requirements into robust technical data models and feature datasets.
• Strong communication skills with the ability to explain technical concepts to actuarial, product, engineering, and security stakeholders.

Preferred Qualifications

• Experience working with insurance, actuarial, claims, pricing, underwriting, mobility, operational, or risk analytics data.
• Experience integrating data from GCP or other cloud platforms into Azure or Microsoft Fabric environments.
• Familiarity with data governance, access control, security configuration, and compliance-oriented data environments.
• Prior experience mentoring junior engineers or leading technical delivery in a cross-functional product environment.