Principal Data Engineer - CX Analytics
Unum Group
- Location
- Portland Maine USA
- Work model
- On-Site
- Level
- Principal
- H-1B history
- 13 approvals (FY2023)
- Posted
- 20h ago
Skills
About this role
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 Principal Data Engineer to join the CX Analytics team within our Customer Experience Organization. In this role, you will lead the design and implementation of 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 build and maintain scalable data pipelines, develop and optimize data models, and integrate new data sources across the ecosystem, including both structured and unstructured data. A core focus of the role is enabling analytics through automation and advancing how we leverage AI—developing and supporting pipelines that incorporate unstructured data and LLM-based workflows to extract signal from sources such as raw text. As a hands-on technical leader, you will define standards and best practices for data engineering while mentoring other engineers and partnering closely with BI Analysts and Data Scientists to support their work. You will help shape how data flows through the team, 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, guide technical direction, and consistently enable the team to deliver high-quality analytics 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 Proactively partner with the business to provide development, construction, testing, and maintenance of data pipelines that support the needs of the business. Integrate large volume of highly complex 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. Build and maintain best practices for team's data engineering strategy; as well as staying informed of best practices across industries and striving for innovation and efficiency. Understand and contribute to the evolution of the enterprise data architecture including the application of current and emerging data frameworks and tools (eg hosting data in