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Closed on September 6, 2026.
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Principal Data Engineer - CX Analytics
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Job Description
Unum Group is hiring a Principal Data Engineer to lead CX Analytics data engineering efforts focused on BI/reporting and advanced analytics.
Responsibilities
- Partner with business teams to deliver development, construction, testing, and maintenance of data pipelines that support business needs.
- Ingest and integrate large volumes of highly complex data from multiple sources, including DB2, SQL Server, Web API, and Teradata.
- Apply validation, aggregation, and reconciliation techniques to build a rich data framework.
- Collaborate with data scientists and business partners to understand business problems and analytics plans, then design data structures aligned to those use cases.
- Establish and maintain best practices for the team’s data engineering strategy; track best practices across industries and drive innovation and efficiency.
- Contribute to the evolution of enterprise data architecture, including adoption of current and emerging frameworks and tools (example: hosting data in Cloud).
- Prepare results for interpretation and/or visualization and communicate potential value to influence strategic decision-making.
- Support integration of solutions into existing business processes using automation techniques.
- Continuously research and build expertise in current and emerging software and data engineering practices.
- Provide support, training, and/or mentorship to lower-level Data Engineer peers.
- Perform other related duties as assigned.
Requirements
- Bachelor’s degree in a quantitative field is required.
- 8 years of professional experience (or equivalent relevant work experience) preferred.
- Expertise in at least one object-oriented programming language: Java/Scala or Python.
- DevOps best practices experience including CI/CD, process automation, and optimization.
- Strong understanding of data architecture principles and infrastructure requirements across on-prem and Cloud platforms.
- Ability to understand and present data in context, including how data will build toward a business solution.
- Preferred: expertise writing complex SQL queries joining multiple tables and databases.
- Independently explore databases/tables or other legacy data to identify best data sources for business problems.
- Demonstrated ability to troubleshoot complex SQL queries with limited guidance.
- Demonstrated ability to create logical data models combining data from multiple sources, including internal and external data.
- Demonstrated communication skills; experience in financial services.
- Leadership experience working with senior management and executive leadership; attention to detail while independently prioritizing work and managing multiple projects simultaneously.
- Ability to understand and explain a problem and identify and communicate an appropriate solution.
- Leader within the field, internally and externally.
- Effective coach and mentor; actively engages peers and team members within areas of expertise.
- Viewed as a leader in change management.
- Maintains depth of technical understanding of third-party and cloud solutions.
- People management: participates in determining staffing needs, including hiring and development.
- Leads assigned team activities and projects to completion.
- Engineering strategic and program management for the organization: coaches, mentors, and helps build team.
- Proactively identifies and researches new approaches and skills needed for data science and advanced analytics.
- Entrepreneurial self-starter.
- Thorough, results-oriented problem-solver and lifelong learner with strong curiosity.
- Deep expertise in their organization.
- Demonstrated ability to conduct independent research and development of techniques that may be shared internally and externally.
Core Data Engineer Capabilities
- Software Engineering: Expertise in at least one object-oriented language (Java/Scala or Python) plus DevOps best practices (CI/CD, automation, optimization).
- Data Architecture and Infrastructure: Understanding of data architecture principles and related infrastructure requirements for on-prem and Cloud.
- Holistic Data Preparation: Ability to frame and present data in the appropriate context for business use.
- Data Extraction, Transform & Load: Complex SQL (multi-table/database joins), independent exploration of legacy data sources, troubleshooting complex SQL with limited guidance, and building logical data models from internal and external sources.
- Core business capabilities: Communication skills, financial services experience, leadership exposure with senior/executive leaders, and ability to prioritize and manage multiple projects.
- Leadership capabilities: Field leader (internal/external), coaching and mentoring, change management leadership, and maintained technical understanding of third-party/cloud solutions.
Technologies
- Java
- Scala
- Python
- CI/CD
- SQL
- DB2
- SQL Server
- Web API
- Teradata
- Cloud
Benefits
- Health insurance
- Vision insurance
- Dental insurance
- Short & Long-Term Disability
- Generous PTO (including paid time to volunteer!)
- Up to 9.5% 401(k) employer contribution
- Mental health support
- Career advancement opportunities
- Student loan repayment options
- Tuition reimbursement
- Flexible work environments
- Performance-based incentive plans
- 401(k) retirement plan with employer match up to 5% and an additional 4.5% contribution whether you contribute to the plan or not
General Summary
- Principal Data Engineer role on the CX Analytics team within Unum’s Customer Experience Organization.
- Lead design and implementation of data solutions enabling BI/reporting and advanced analytics with data that is accessible, reliable, and structured for use.
- Build and maintain scalable data pipelines, optimize data models, and integrate new structured and unstructured sources across the ecosystem.
- Enable analytics through automation and advance AI usage, including pipelines that incorporate unstructured data and LLM-based workflows to extract signal from sources such as raw text.
- Define data engineering standards and best practices while mentoring engineers and partnering with BI Analysts and Data Scientists.
- Shape how data flows through the team to ensure environments, pipelines, and datasets emphasize quality, scalability, and usability.
- Campus-based role; current remote and field-based Unum employees may apply and will be considered per company policy.