Engineering Manager, Data

Super.com is hiring an Engineering Manager, Data to lead Finance Automation within Data Engineering. The role leads a team responsible for financial data, dbt models, pipelines, and NetSuite syncs that support accounting close, while shaping the team’s technical roadmap and delivery practices.

Responsibilities:

• Oversee a full-stack team of 5+ data engineers or analytics engineers. You will be responsible for the continued staffing of the team, including being a key contributor to hiring processes
• Propel the business and engineering org forward by leading high-impact transformational projects end-to-end in an iterative, data-driven, startup environment
• Shape the technical roadmap for the team, contribute to product roadmap and OKR discussions, and drive the engineering agile processes for the team
• Contribute to a culture of continuous improvement and growth, ensuring team members excel with oversight and mentorship, are working on projects at the intersection of interest, experience, and business impact, and have concrete opportunities for growth
• Drive high release quality and cadence by completing code reviews, ensuring end-to-end tests are written, and sustainable yet pragmatic development practices are followed
• Strategically contribute technically - write important design docs, tackle particularly intricate components / features or services, jumping in as an individual contributor when appropriate

Requirements:

• 5+ years experience as a data or analytics engineer
• at least 2 year experience as a people leader
• 5+ years building production data pipelines and warehouse models, with strong SQL and working dbt proficiency
• You can review a model and catch grain, fan-out and testing gaps
• Experience owning financial data that Accounting depends on: GL feeds, month-end close, reconciliation, audit support, payment processing
• Evidence of designing and implementing logical, well-architected solutions for complex, large-scale data engineering challenges
• Deep experience in database design & warehouse data modeling, scheduling & orchestration
• A track record of turning ambiguous stakeholder requests into scoped, estimated plans, and pushing back when capacity is short
• Clear communication with both accountants and engineers