Manager, Data Engineering

Skillable is a 100% remote and virtual tech company that’s modernizing the world of training. Come share your professional magic with highly talented, driven and fun colleagues who believe in the power of “skilling.” Experience what a team focused on doing the right thing feels like!

Our talented people are what makes us friendly and have fun! We work together to create amazing solutions and experiences for our customers and their clients. We utilize our employees’ personal strengths to help grow our company and ensure our team is living their best, authentic life. We share our appreciation for our team members regularly during all-hands, a workplace appreciation tool, regular shoutouts in our Teams channels, social media, amongst more. Our remote-first work environment blends work and life without the added pressure of commuting or feeling guilty about leaving early to visit the dentist.

Come work with us and learn what teamwork and integrity blended with an emphasis on well-being and balance can do for your career and lifestyle!

The Manager, Data Engineering, is responsible for turning data architecture vision into reliable, repeatable, and scalable data pipelines and data products as part of Skillable’s enterprise data platform. Manage a team of at least five employees and be hands-on in technical ownership of the data engineering function. Lead day-to-day engineering execution while setting strong data engineering practices across ingestion, transformation, testing, deployment, and operational support.

What You Will Do:

• Manage a team by hiring and onboarding talent, setting clear expectations, conducting formal performance reviews, and coaching accountability. 

• Lead the team to deliver on the enterprise data platform roadmap by translating architecture direction into sequenced execution plans, team backlogs, and measurable outcomes.  

• Create a strong engineering culture across the team by setting standards for maintainability, organization, and repeatability; growing engineers via regular 1:1s, timely feedback, development plans, and formal review cycles; and being responsible for overall team performance and cohesion. 

• Own day-to-day execution for the Data Engineering team by breaking work into tasks, driving sprint-level planning, delegating effectively to grow ownership, unblocking delivery, and ensuring high-quality outcomes through engineering reviews and feedback. 

• Drive implementation of the Medallion architecture (Bronze → Silver → Gold) with strong enforcement of layer responsibilities, ensuring repeatable and auditable pipeline behavior leveraging Boomi, Dbt, Azure Data Bricks, Boomi/Rivery, Delta tables, and Sql Server. 

• Partner closely with the Data Architect to bring the architecture to life through concrete implementation patterns, reference pipelines, and guardrails—ensuring the team can consistently execute the intended approach. 

• Reduce friction by driving crisp decisions and forward motion—using lightweight decision records, seeking the right input, and then executing accountability (while avoiding overly heavy process).  

• Establish DataOps practices aligned with modern software development lifecycle (SDLC): CI/CD for data assets, consistent branching/release patterns, code review standards, and runbooks/operational readiness for pipelines.  

• Improve