Principal Data Engineer

Position Summary

The Principal Data Engineer serves as a senior technical leader responsible for architecting, developing, and governing enterprise‑scale data platforms, pipelines, and analytics solutions. This role provides hands‑on technical leadership across data engineering initiatives, cloud modernization efforts, real‑time integrations, and enterprise data strategy. The ideal candidate combines deep expertise in modern data engineering technologies with strong leadership capabilities to guide engineering teams, establish best practices, and deliver scalable, secure, and high‑performing data solutions that support analytics, reporting, AI/ML, and operational business functions.

• Design, build, and optimize enterprise‑scale data pipelines and integration frameworks supporting analytics, reporting, operational, and AI/ML workloads.
• Architect scalable data lake, warehouse, and real‑time streaming solutions using cloud‑native technologies.
• Design and maintain logical and physical data models aligned with enterprise architecture standards and normalization best practices.
• Build robust ingestion, transformation, orchestration, and delivery pipelines across structured and semi‑structured data sources.
• Integrate data from core insurance systems (policy admin, claims, billing, CRM) and third‑party sources.
• Serve as the technical lead for data engineering initiatives and provide architectural guidance across engineering teams.
• Mentor and coach junior and mid‑level engineers, promote coding standards, CI/CD, infrastructure as code, monitoring, observability, and operational support.
• Lead design reviews, technical solutioning sessions, and enterprise architecture discussions.
• Develop cloud‑native data solutions using AWS, Azure, Snowflake, Spark, Kafka, Airflow, Glue, and related technologies.
• Drive modernization initiatives involving hybrid‑cloud and multi‑cloud architectures.
• Build reusable frameworks and automation solutions to improve scalability, reliability, and engineering productivity.
• Integrate enterprise data from core operational systems, third‑party vendors, APIs, and streaming platforms.
• Develop and optimize ETL/ELT pipelines using SQL, Informatica/IICS, Python, Spark, and cloud‑native processing tools.
• Ensure high‑performance query optimization, workload tuning, and efficient data processing across enterprise platforms.
• Implement data governance, security, and compliance, including metadata management, lineage, auditing, and observability.
• Partner with cybersecurity, governance, and compliance teams to enforce secure and compliant data engineering practices.
• Collaborate with architects, analysts, actuaries, data scientists, developers, and business stakeholders to deliver scalable and trusted data solutions.
• Translate complex business requirements into enterprise data architectures and engineering solutions.
• Support strategic initiatives such as underwriting analytics, claims automation, customer analytics, and regulatory reporting.
• Provide mentorship and architectural oversight to junior and mid‑level engineers across teams.
• Work in a hybrid environment out of a local Kemper office (Chicago or Downers Grove, IL) or remotely for eligible non‑local candidates.

• 10+ years of experience in data engineering, data architecture, or software engineering.
• Expert‑level experience with SQL, Python, Snowflake, and enterprise ETL/ELT frameworks.
• Hands‑on experience with cloud‑native data engineering tools and platforms (AWS Glue, S3, Snowflake, Kafka, Airflow).
• Proven experience leading large‑scale enterprise data initiatives and mentoring engineering teams.
• Strong understanding of data governance, security, scalability, and performance optimization.
• Experience working in regulated industries and familiarity with data privacy, security, and compliance frameworks (HIPAA, SOX, GDPR, NAIC).
• Strong understanding of insurance industry data (especially P&C and Life domains), including policy admin systems such as Guidewire, Life/400, claims platforms, and actuarial models.
• Preferred:
  Experience with real‑time streaming and event‑driven architecture, Spark, Kafka, Airflow, DBT, Infrastructure as Code frameworks, Dev Ops, CI/CD pipelines, IDMC/IICS, and Data Vault 2.0.
• Knowledge of Git for version control and collaboration.
• Bachelor’s or master’s degree in computer science, engineering, information systems, data science, or related field, or equivalent work experience.

• Competitive salary range: $111,900 to $186,700.
• Annual discretionary bonus.
• Medical, dental, vision coverage, paid time off, and 401(k).

All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, disability status or any other status protected by the laws or regulations in the locations where we operate. Kemper is an equal opportunity employer.