Unum · Columbia, SCPrepare for this interview
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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: This position for a data Engineer who will design, build and maintain data systems and pipelines to allow data to be accessed and utilized optimally for analytics or visualization/insight generation purposes. The role requires technical expertise in the fields of computer programming, database management and data architecture; and relies on increasing business knowledge. With some support from manager, this individual will build and execute data engineering approaches to support business priorities. Job Specifications Bachelor's degree in quantitative field or equivalent experience 2 years of professional experience or equivalent relevant work experience preferred Core Data Engineer Capabilities: Knowledge in all of the following skillsets and deep expertise in at least two: Data Engineering: Experience with at least one relevant ETL toolset (IICS, Python, SnowSQL, etc.). 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: Preferred skills include: Experience in writing complex SQL queries that join multiple tables/databases. Experience exploring databases/tables or other legacy data content to identify best data sources to solve business problems. 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. Domain Knowledge: Deep understanding of Fineos and experience with Snowflake Cortex AI preferred. 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. Ability to understand and explain a problem and identify and communicate an appropriate solution. Leadership Capabilities : Developing ability to coach or mentor team members, ability to commit quickly and positively to change. Viewed as embracing change and leading proof of concept work and prototyping when necessary Preferred characteristics: Entrepreneurial self-starter, a thorough, results-oriented problem-solver, and a lifelong learner with voracious curiosity AND basic understanding of their organization Principal Duties and Responsibilities 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 Snowflake, Fineos, 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. 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 architectur
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