Analytics Engineer

Church Mutual Insurance Company, S.I.•Milwaukee, WI

2d•Hybrid

About The Position

The Analytics Engineer develops and maintains enterprise analytics solutions using Microsoft Fabric, Python, SQL, and modern BI tools to support data and reporting needs across all functional areas of the company including Underwriting, Claims, Finance, Risk, Operations, and Distribution. This role is responsible for building scalable data models, pipelines, and semantic layers within Microsoft Fabric to enable self-service analytics and high-quality data delivery across the organization. This role will also support the modernization of the organization's analytics ecosystem by driving adoption of Microsoft Fabric capabilities including OneLake, Lakehouse architecture, Data Pipelines, Notebooks, and governance standards.

Requirements

Bachelor's degree in Data Analytics, Data Science, Statistics or related field. May consider equivalent experience in lieu of a degree.
Three or more years of experience in data engineering, analytics engineering, business intelligence, or a related field are required, preferably an analytical role in a property and casualty insurance setting.
In‑depth knowledge of insurance business functions, operations, objectives, and information flow, specific knowledge of underwriting processes is preferred.
Strong hands-on experience with Microsoft Fabric, including Lakehouse, Pipelines, Delta tables, Dataflows Gen2, and semantic modeling.
Proficiency with Python for data preparation, automation, and analytics workflows.
Strong SQL skills and experience working with relational, cloud, or big data platforms.
Experience building or managing BI models and reports (Power BI preferred).
Familiarity with modern data engineering patterns, including ELT, Lakehouse architecture, and version-controlled analytics workflows.
Ability to communicate complex technical concepts to non-technical audiences.
Experience with data governance, data quality management, and metadata concepts is preferred.
Knowledge of insurance operations is helpful but not required.
Strong collaboration skills and the ability to support and mentor others.

Nice To Haves

specific knowledge of underwriting processes is preferred.
Experience with data governance, data quality management, and metadata concepts is preferred.
Knowledge of insurance operations is helpful but not required.

Responsibilities

Design, build, and maintain scalable data pipelines and Lakehouse architecture within Microsoft Fabric.
Develop semantic models, datasets, and reusable analytics assets leveraging Fabric's Lakehouse, Warehouse, Pipelines, and Dataflows Gen2.
Implement data transformations and automation using Python, SQL, and Fabric Notebooks.
Create and optimize Fabric data engineering workflows, including ingestion, transformation, orchestration, and monitoring.
Partner with business leaders across the enterprise to translate analytics needs into scalable data solutions.
Develop dashboards and analytical reports using Power BI as the primary visualization layer on top of Fabric datasets.
Ensure data reliability and quality through validation, profiling, documentation, and monitoring practices.
Collaborate closely with IT, Data Engineering, and business units to understand data sources, resolve data issues, and improve data accessibility.
Support Fabric workspace provisioning, governance, security configuration, and lifecycle management.
Contribute to the development of enterprise data governance standards, metadata practices, and data cataloging.
Provide guidance, coaching, and training to business teams on Fabric and modern analytics tooling.
Support enterprise data modernization initiatives and cross-functional analytics projects.