Senior Data Engineer

Unum Group • Atlanta, GA

2d

About The Position

The Senior Data Engineer is an experienced, 100% hands-on technical lead for data engineering across assigned Value Streams, providing technical leadership across at least two Value Streams. The role translates enterprise architecture standards, patterns, and governance guardrails into detailed, production-ready designs that engineering teams can implement. The engineer actively designs solutions, resolves complex engineering challenges, makes technical decisions, reviews code and implementations, and guides engineers through delivery.

The role leads the design and delivery of complex data pipelines, ETL/ELT processes, data warehouses, data marts, data models, and integration solutions using technologies including Snowflake, SQL, Python, and modern ETL/ELT tooling. It partners with architects, product owners, engineers, analysts, and business stakeholders to deliver scalable, reliable, secure, and maintainable solutions. The position also advances Value Stream transformation by establishing engineering best practices, leading design and code reviews, mentoring engineers, and promoting consistency and technical excellence across teams.

Requirements

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field is preferred.
• At least 6 years of experience in Data Engineering, Software Engineering, Data Integration, or related technical disciplines.
• Hands-on experience designing and building complex data pipelines, ETL/ELT solutions, data warehouses, data marts, and data models in large-scale enterprise environments.
• Strong hands-on expertise with Snowflake, SQL, Python, and modern ETL/ELT technologies.
• Experience with cloud data platforms and data integration through APIs and batch, near-real-time, and real-time patterns.
• Deep knowledge of data modeling, data integration patterns, solution design, and modern data engineering practices.
• Ability to translate enterprise architecture patterns, standards, and guardrails into detailed, scalable, production-ready technical designs.
• Experience as a hands-on technical lead, making design decisions, conducting design and code reviews, resolving complex engineering problems, and guiding engineers through implementation.
• Strong understanding of DevOps and CI/CD practices, Git, automated testing, automation, deployment, and operational excellence.
• Experience delivering solutions in complex enterprise data environments involving multiple systems, platforms, and data sources.
• Ability to mentor engineers and influence technical direction while remaining actively involved in engineering delivery.
• Strong problem-solving, communication, and stakeholder management skills.
• Strong business acumen and ability to balance technical quality, delivery objectives, and business outcomes.

Nice To Haves

• Familiarity with legacy data platforms such as Teradata and DB2, particularly in modernization or transformation environments.

Responsibilities

• Serve as hands-on technical lead for data engineering across assigned Value Streams, providing technical direction across at least two Value Streams.
• Lead the design and implementation of complex data engineering solutions, including data pipelines, ETL/ELT processes, data warehouses, data marts, data models, and enterprise data assets.
• Translate enterprise architecture standards, patterns, and governance guardrails into detailed, scalable, implementable technical designs.
• Contribute actively to solution design and engineering, troubleshoot complex technical challenges, and guide solutions through implementation and production.
• Make key technical design decisions and lead design and code reviews to ensure scalability, reliability, security, performance, and maintainability.
• Lead complex integrations across cloud, on-premises, internal, and external data sources, including batch, near-real-time, real-time, and API-based integrations.
• Partner with architects, product owners, analysts, engineers, and business stakeholders to understand requirements and determine appropriate technical solutions.
• Establish and promote engineering best practices for data modeling, integration, automation, testing, performance optimization, deployment, and operational support.
• Guide engineers through implementation and provide hands-on technical coaching and mentoring.
• Support Value Stream transformation through adoption of modern data engineering patterns, technologies, and development practices.
• Apply approved AI-enabled tools where appropriate to improve engineering productivity, quality, and delivery.

Benefits

• Award-winning culture and inclusion and diversity as a priority.
• Performance-based incentive plans.
• Health, vision, and dental benefits.
• Short- and long-term disability insurance.
• Generous paid time off, including paid time to volunteer.
• 401(k) employer contribution: up to 9.5% described in the opening benefits list; the later benefits details specify an employer match up to 5% plus an additional 4.5% contribution whether or not the employee contributes.
• Mental health support.
• Career advancement opportunities.
• Student loan repayment options.
• Tuition reimbursement.
• Flexible work environments.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior