Manager, Data Engineering

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Manager, Data Engineering based in the United States.

This is an exciting opportunity for an experienced data engineering leader to shape and scale an enterprise data platform within a fully remote, technology-driven organization. You will lead a team of at least five engineers, translating data architecture strategy into reliable, scalable, and maintainable data pipelines and products. Combining hands‑on technical expertise with people leadership, you will drive engineering execution, establish best practices, and improve the quality and predictability of delivery.

You will oversee modern lakehouse implementations, strengthen data governance, and ensure pipelines are secure, observable, and operationally reliable. Working closely with data architects, application teams, and business stakeholders, you will transform complex requirements into practical solutions that support informed decision‑making. This role offers the opportunity to mentor engineers, develop future leaders, and foster a culture of accountability, collaboration, and continuous improvement while enjoying the flexibility of a remote‑first environment.

• Lead, manage, and develop a team of at least five data engineers by overseeing hiring, onboarding, performance reviews, coaching, professional development, and accountability.
• Translate enterprise data architecture strategy into actionable roadmaps, prioritized backlogs, sprint plans, and measurable delivery outcomes that align with business objectives.
• Oversee day‑to‑day engineering execution by breaking initiatives into manageable tasks, delegating responsibilities, removing blockers, conducting technical reviews, and ensuring high‑quality deliverables.
• Establish engineering standards that promote maintainability, consistency, documentation, repeatability, and predictable delivery across the data engineering function.
• Drive implementation of the Medallion architecture (Bronze, Silver, and Gold) using technologies such as Azure Databricks, Spark, Delta Lake, SQL Server, dbt, Boomi, and Rivery, ensuring clear separation of responsibilities between data layers.
• Partner closely with the Data Architect to translate architectural principles into practical implementation patterns, reference pipelines, and technical guardrails that support consistent execution.
• Establish modern Data Ops practices aligned with the software development lifecycle, including continuous integration and continuous delivery (CI/CD), branching and release strategies, code review standards, and operational runbooks.
• Improve pipeline observability and reliability by implementing monitoring for data freshness, pipeline failures, and data quality, while ensuring predictable incident response and operational support.
• Collaborate with application and database teams to establish efficient, non‑disruptive data access patterns for upstream SQL Server systems, including change data capture (CDC), read replicas, snapshot isolation, and batching strategies.
• Design and oversee ingestion and transformation workflows for diverse source systems, including APIs, CDC‑enabled databases, and file‑based data feeds, selecting appropriate approaches based on source requirements.
• Work with business stakeholders to clarify requirements, manage incoming requests, reduce unplanned work, and prioritize initiatives that align with platform strategy and delivery capacity.
• Promote efficient decision‑making through clear communication, lightweight documentation, appropriate stakeholder input, and ownership of agreed actions.
• Build a strong engineering culture through regular one‑on‑one meetings,…