Lead Cloud Data Engineer

The Mutual Group • Chicago, IA

55d • $140,000 - $165,000 • Hybrid

About The Position

We are building a next-generation Cloud Data Platform to unify data from Policy, Claims, Billing, and Administration systems into a single source of truth. As a Lead Cloud Data Engineer, you will play a key role in supporting The Mutual Group (TMG), GuideOne Insurance, and future members by designing, building, and optimizing our modern data ecosystem leveraging Medallion architecture, Delta Lake, and modern data warehouse technologies such as Snowflake, Synapse, or Redshift. As a technical leader, the Lead Data Engineer will define and execute the end-to-end data engineering strategy from data ingestion and modeling to governance and performance optimization enabling scalable, high-quality, and analytics-ready data assets. This role requires hands on deep technical expertise in cloud-native data engineering, automation, and architecture design, coupled with strong leadership to mentor teams and align solutions with business goals. Work Arrangement: Employees who live within 30 miles of the TMG home office are expected to follow a hybrid or in-office schedule. The initial training period may require additional in‑office days.

Requirements

• Bachelor’s or master’s degree in computer science, Data Engineering, or a related field.
• 12+ years of experience in data engineering with at 3+ years in a lead or architect-level role and least 8+ years on cloud platforms (AWS, Azure, or GCP).
• Deep hands-on experience with Python, SQL, and data modeling (relational, and Dimensional), Databricks, Spark, AWS Glue, Delta Lake, Snowflake, Synapse, or Redshift
• Proven experience with Medallion architecture, modern data warehousing principles., data governance, lineage, and CI/CD for data pipelines
• Excellent leadership, communication, and cross-functional collaboration skills.

Nice To Haves

• Experience in the Property & Casualty (P&C) Insurance domain such as Policy, Claims, or Billing data preferred.
• Familiarity with event-driven architectures (Kafka, Kinesis) and real-time data streaming.
• Knowledge of machine learning pipeline integration and feature engineering.
• Proven ability to lead large-scale data modernization or cloud migration initiatives.

Responsibilities

• Data Platform Design & Architecture Define the strategic roadmap for the enterprise data platform, ensuring scalability, performance, and interoperability across business domains.
• Architect and implement cloud-native, Medallion-based data architectures (Bronze–Silver–Gold layers) for unified and governed data delivery.
• Drive standardization of data models, pipelines, and quality frameworks across Policy, Claims, Billing, and Administrative data assets.
• Evaluate and implement emerging data technologies to strengthen the platform’s performance, cost efficiency, and resilience
• Data Integration & Ingestion Design, build, and optimize high-performance ingestion pipelines, using AWS Glue, Databricks, or custom Spark applications.
• Automate ingestion of structured, semi-structured, and unstructured data from APIs databases, and external data feeds.
• Tune and monitor ingestion pipelines for throughput, cost control, and reliability across dev/test/prod environments.
• Data Transformation & Modeling Hands on Development of ETL/ELT pipelines using Databricks or similar frameworks to transform raw data into curated and consumption-ready datasets.
• Design and develop relational, Vault, and dimensional data models to support analytics, BI, and AI/ML workloads.
• Define and enforce data quality standards, validation frameworks, and enrichment rules to ensure trusted business data.
• Apply data quality, cleansing, and enrichment logic to ensure accuracy and completeness of business-critical data.
• Cloud Infrastructure, Automation and Performance Collaborate with DevOps and Cloud Engineering teams to design automated, infrastructure-as-code environments using Terraform, CloudFormation, or equivalent tools.
• Implement CI/CD pipelines for data pipeline deployment, versioning, and testing.
• Lead performance tuning and scalability optimization to ensure highly available, cost-efficient data platform.
• Governance, Security & Compliance Implement and enforce data governance, cataloging, and lineage practices using tools such as Purview, Alation, or Collibra.
• Partner with InfoSec to implement data privacy, access control, and compliance frameworks aligned with regulatory standards.
• Drive consistency and accountability in data stewardship across business and IT teams.
• Leadership, Collaboration & Mentorship Lead a team of data engineers, providing technical guidance, coaching, and performance mentorship.
• Collaborate with Data Architects, Analysts, and Business Leaders to align data solutions with enterprise strategy.
• Promote a culture of engineering excellence, reusability, and knowledge sharing across data organization.
• Influence enterprise-wide standards for data engineering, automation, and governance.

Benefits

• Competitive base salary plus incentive plans for eligible team members
• 401(K) retirement plan that includes a company match of up to 6% of your eligible salary
• Free basic life and AD&D, long-term disability and short-term disability insurance
• Medical, dental and vision plans to meet your unique healthcare needs
• Wellness incentives
• Generous time off program that includes personal, holiday and volunteer paid time off
• Flexible work schedules and hybrid/remote options for eligible positions
• Educational assistance

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level