Data Engineer II

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:

AI is a fundamental, transformational technology like the Internet, personal computers, and electricity. This position is your opportunity to get into AI during these chaotic early and exciting times. The Data Engineering role is a critical one for the Advanced Analytics team. Data is the fuel that will drive AI/ML models to bring transformative value and this role will be responsible for the creation, understanding, and maintenance of data lakes to be used by data scientists for algorithm development. In addition, the data engineer will need to be able to work closely with the business to understand the business process, how data is created, where it is stored, and how we can leverage it for AI/ML models. This role will work closely with AI product managers, data scientists, and business analysts to perform their function.

This hybrid position is only available out of our Chattanooga, TN office and requires at least two in-office days per week.

Job Specifications

• 2+ years technical Data Science industry experience
• 2+ in SQL, Python, or other data engineering-based computer language
• Ability to prioritize and coordinate tasks to meet multiple deadlines
• Comfortable with ambiguity, adaptable to a high-change environment, and open to new concepts and processes
• Familiarity with Python computing stack, AWS, and Snowflake
• Experience with scripting and data analysis programming languages, such as Python or R
• Advanced proficiency with SQL and data visualization tools (e.g., Tableau, Mode, etc.)
• Strong intellectual curiosity with a healthy dose of skepticism
• Excellent written and verbal interpersonal communication skills
• Basic statistics skills acquired through academic study (i.e., math, computer science, engineering, economics, physics, operations research) or comparable work experience
• Basic knowledge of computer programming, software engineering, DevOps / MLOps practices
• Strong Business Acumen with understanding business concepts, practices, and business domain language to engage in problem solving sessions and discuss business issues in stakeholder language
• Demonstrated commitment to learning through your own initiatives through courses, books, or side projects
• Previous insurance industry experience highly preferred.
• Databricks or similar data lake house automation experience preferred
• Microsoft Azure or TensorFlow Machine Learning suite experience preferred

Principal Duties and Responsibilities

• Work closely with AI product managers, data scientists, and key business stakeholders to understand the creation, flow, and usage of data.
• Data engineer will create data dictionaries, document system of records for data, and work closely with data scientists on feature engineering data to be used by advanced machine-learning algorithms.
• Identify, implement, and improve data models and methodologies that enable a world class data science engine to run.
• Create and manage data pipelines into a cloud-based data science instance (AWS).
• Work closely with business to understand context on business process, data creation, and feasibility of A