[Remote] Principal Data Engineer

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