Unum is a Fortune 500 company committed to providing employee benefits and service solutions. The Data Engineer I will design, build, and maintain data systems and pipelines to ensure data accessibility and optimization for analytics and insights.
Employ a variety of languages and tools to develop, construct, test and maintain data pipelines, ensuring they support the requirements of the business.
Integrate varying sizes of data from different sources (including DB2, SQL Server, Web API and Teradata, Snowflake).
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.
Create data assets that conform to scalability, extensibility, performance and maintainability requirements for the problem at hand. Promotes development of solutions following appropriate engineering process that is fit to purpose for different use scenarios.
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 Cloud).
Efficiently prepares results for interpretation and/or visualization and communicates findings and potential value to manager.
Support integration of solutions within existing business processes using automation techniques.
Understand theory and application of current and emerging software engineering practices.
Provides support to lower level Data Engineer peers.
Perform other related duties as assigned
Qualification
Required
Bachelor’s degree in quantitative field is required
Experience with tools and platforms such as Teradata, Snowflake, Alteryx, and Python
Core Data Engineer Capabilities: Knowledge in all of the following skillsets and deep expertise in at least two
Software Engineering: Experience in Python. Exposure to DevOps best practice including CI/CD, process automation and optimization
Data Architecture and Infrastructure: Understanding of data architecture principles and related infrastructure requirements, covering on-prem and Cloud platforms
Holistic Data Preparation: The ability to understand and present data, including a basic understanding of how the data will build towards a business solution
Data Extraction, Transform & Load: Experience in writing complex SQL queries that join multiple tables/databases
Core business capabilities: Demonstrated communication skills, experience in financial services, exposure to working with senior management and executive leadership, and attention to detail while effectively prioritizing work and managing multiple projects simultaneously
Leadership Capabilities: Developing ability to coach or mentor team members, ability to commit quickly and positively to change
Employ a variety of languages and tools to develop, construct, test and maintain data pipelines, ensuring they support the requirements of the business
Integrate varying sizes of data from different sources (including DB2, SQL Server, Web API and Teradata, Snowflake)
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
Create data assets that conform to scalability, extensibility, performance and maintainability requirements for the problem at hand
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 Cloud)
Efficiently prepares results for interpretation and/or visualization and communicates findings and potential value to manager
Support integration of solutions within existing business processes using automation techniques
Understand theory and application of current and emerging software engineering practices
Provides support to lower level Data Engineer peers
Preferred
Master’s is preferred
2+ years of professional experience or equivalent relevant work experience preferred
Demonstrates ability to troubleshoot complex SQL queries with little guidance
Demonstrates ability to create logical data models by combining data from multiple sources including internal and external data
Preferred characteristics: Entrepreneurial self-starter, a thorough, results-oriented problem-solver, and a lifelong learner with voracious curiosity AND basic understanding of their organization
Benefit
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.
Since our founding in 1848, Unum has been a leader in the employee benefits business through innovation, integrity and an unwavering commitment to our customers.
