Note: The job is a remote job and is open to candidates in USA. Kemper is one of the nation’s leading specialized insurers, and they are seeking a Principal Data Engineer to serve as a senior technical leader responsible for architecting, developing, and governing enterprise-scale data platforms. The role involves providing hands-on technical leadership across data engineering initiatives, cloud modernization efforts, real-time integrations, and enterprise data strategy.
Responsibilities
- Design, development, 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
- Architect cross-functional data solutions that integrate data from core insurance systems (e.g., 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 while promoting engineering excellence and continuous improvement
- Establish best practices for 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, and modern data platforms including 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
- Ensure compliance with enterprise security standards, governance policies, and regulatory requirements including HIPAA, SOX, GDPR, and NAIC standards applicable
- Implement data quality, metadata management, lineage, auditing, and observability capabilities
- 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 including underwriting analytics, claims automation, customer analytics, and regulatory reporting
- Provide technical mentorship and architectural oversight to junior and mid-level engineers across teams
Skills
- 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 (e.g., 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 understanding data privacy, security, and compliance frameworks
- Strong understanding of insurance industry data (especially P&C and Life domains), including data from policy admin systems (e.g., Guidewire, Life/400), claims platforms, and actuarial models
- Bachelor's or master's degree in computer science, Engineering, Information Systems, Data Science, or related fields or equivalent work experience
- Insurance industry experience (P&C and/or Life) preferred
- Experience with real-time streaming and event-driven architecture a plus
- Experience in Spark, Kafka, Airflow, DBT, and Infrastructure as Code frameworks preferred
- Experience in working with IDMC/IICS or DBT a plus
- Experience in Data warehousing with Data vault 2.0 preferred
- Familiarity with DevOps and CI/CD pipelines for data engineering platforms
Benefits
- Annual discretionary bonus
- Medical
- Dental
- Vision
- PTO
- 401k
Company Overview