Sr. Data Engineer - CX Analytics

Job Posting End Date: August 15

When you join the team at Unum, you become part of an organization committed to helping you thrive.

Here, we work to provide the employee benefits and service solutions that enable employees at our client companies to thrive throughout life’s moments. And this starts with ensuring that every one of our team members enjoys opportunities to succeed both professionally and personally. To enable this, we provide: 

• Award-winning culture 

• Inclusion and diversity as a priority 

• Performance Based Incentive Plans

• Competitive benefits package that includes: Health, Vision, Dental, 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 

*All the benefits listed above are subject to the terms of their individual Plans.

And that’s just the beginning…  

With 10,000 employees helping more than 39 million people worldwide, every role at Unum is meaningful and impacts the lives of our customers. Whether you’re directly supporting a growing family, or developing online tools to help navigate a difficult loss, customers are counting on the combined talents of our entire team. Help us help others, and join Team Unum today! 

General Summary:

We are seeking a Senior Data Engineer to join the CX Analytics team within our Customer Experience Organization. In this role, you will design, build, and maintain data solutions that enable BI/reporting and advanced analytics across the team, ensuring data is accessible, reliable, and structured for meaningful use across our team. You will own specific data domains and pipelines end-to-end, develop and optimize data models, and integrate new data sources across the ecosystem, including both structured and unstructured data. A core expectation of the role is building and supporting AI-enabled pipelines and LLM-based workflows that extract signal from sources such as raw text, alongside broader automation that scales how the team delivers analytics.

As a hands-on builder, you will spend your time close to the work—writing code, developing pipelines, and solving technical problems daily—while helping shape standards and best practices for data engineering as the team grows. You will mentor other engineers and partner closely with BI Analysts and Data Scientists to support their work, ensuring environments, pipelines, and datasets are built with quality, scalability, and usability in mind. The ideal candidate is a strong problem solver and collaborator who can work across technologies and data domains, take ownership of complex work, and consistently deliver data solutions that support better decision-making across the organization.

This is a campus-based role. Current remote and field-based Unum employees may apply and will be considered in accordance with company policy.

Principal Duties and Responsibilities

• Employ a variety of languages and tools to lead the development, construction, testing and maintenance of complex data pipelines, ensuring they support the requirements of the business.

• Efficiently integrate large volume of data from different sources (including DB2, SQL Server, Web API and Teradata).

• Apply validation, aggregation, and reconciliation techniques to create a rich data framework.

• Work closely with the data scientists and business partners to understand the business problem they are trying to solve and the analytics solutions they plan to apply. Use this understanding to create appropriate data structures tailored for the specific problem.

• Define scalability, extensibility, performance and maintainability requirements for the problem at hand and create data pipelines meeting requirements. Promote and lead development of solutions following appropriate engineering process that is fit to purpose for different use scenarios.      

• Gain a deep understanding of and drive the evolution of the enterprise data architecture  including the  application of current and emerging data frameworks and tools (eg hosting data in Cloud).

• Efficiently prepares results for interpretation and/or visualization and  communicates findings and potential value to influence manager, leadership, and business partner decision making.

• Play a lead role in integration of solutions within existing business processes using automation techniques. 

• Gain a deep understanding