Data Engineering Manager | Client Services

Position: Data Engineering Manager | Home Client Services
Location: New York

The Red Ventures Home Client Services group is looking for a Data Engineering Manager to lead a team of up to four data engineers building the data platform that powers our home services business. In this role, you'll translate business strategy into executable technical plans across a modern lakehouse stack, serve as a credible technical point of contact for external clients and internal stakeholders, and push the team toward an AI-forward way of working.

You'll bring enough technical depth to coach and redirect, and enough business fluency to engage early and drive real impact.

Curious how Home fits into Red Ventures? . This role is open to remote or hybrid candidates (East Coast preference), with hybrid being central to our New York, NY or South Charlotte area offices. This role is not open to visa sponsorship or transfer of visa sponsorship including those on H1-B, F-1, OPT, STEM-OPT, or TN visa, nor is it available to work corp-to-corp.

What You’ll Do:

Lead a team of 2-4 Data Engineers with varied experience levels to design and build data pipelines from various data sources to a target data warehouse using real-time and batch data load strategies utilizing modern cloud technologies

Serve as a people leader through servant leadership, supporting formal performance review cycles, providing regular actionable feedback, and actively investing in each engineer's career development and long-term growth

Own the design and delivery of data platform solutions end to end: from ingestion and transformation to outgestion, scheduling, alerting, and monitoring, ensuring the platform reliably serves business needs at scale

Build and maintain strong relationships across business, client, and technical stakeholders, translating business strategies and requirements into a forward-looking technical roadmap, holding the team accountable to delivering against it, and serving as a credible, trusted point of contact who knows when and how to push back Establish and enforce standards for data governance, documentation, data quality, and pipeline observability, including lineage, access control, metadata, and end-to-end integration workflows

Drive operational excellence across the platform: reliability, scalability, performance, cost optimization, and proactive monitoring and alerting practices

Lead and execute proof-of-concepts where appropriate to assess, validate, and improve technical processes and approaches

Spot and champion opportunities to build AI into the data stack, push the team toward agentic tooling and AI-assisted pipeline development, and model an AI-forward approach to how the work gets done Engage early with business stakeholders to understand how data is used and created across the organization, surface opportunities to deliver more value upstream, and keep data engineering involved before requirements are locked

What We’re Looking For:

3+ years managing a data engineering team, plus at least 5 years of hands-on data engineering experience before or alongside that management experience4+ years of hands-on Databricks experience, including Unity Catalog, Delta Lake, and workflow orchestration, with the ability to architect solutions within the platform4+ years working on cloud technologies: AWS preferred, Azure or GCP experience welcome

Strong hands-on coding experience with Python and PySpark in a distributed computing context

Strong background in code-first data transformation workflows, scalable data modeling, and data quality best practices

Deep expertise in data governance, including data quality standards, lineage, access control, and documentation, and a track record of holding a team accountable to those standards

Experience with pipeline observability and monitoring practices: knows what…