Senior Engineering Manager, Data Engineering

Are you an engineering leader who cares deeply about how data is defined, governed, and made accessible at platform scale? Do you know how to hire and develop engineers with deep data systems expertise, engage credibly in architecture conversations, and create the conditions for your team to do their best work? Do you thrive on building organizations whose output becomes the foundation every product team depends on? If so, we'd love to talk.

As a Senior Engineering Manager at Ridgeline, you will lead the team responsible for Ridgeline's data access and semantics layer — the infrastructure that defines what data means, governs how it's written, and standardizes how it's read across the platform. This is high-leverage work: the contracts and access patterns your team establishes become the defaults every product team builds on.

You will lead a team of engineers, supporting their growth and success while partnering with engineering staff and leadership across the organization, to drive data contract adoption, evolve the query interface into the universal data access layer, and build toward a federated query capability that spans the full persistence layer.

At Ridgeline, how we work matters as much as what we build. Ridgeliners act like owners, choose growth over comfort, and communicate with transparency. We assume positive intent, bias toward action, and bring solutions — not just problems. We celebrate wins, learn from setbacks, and thrive in a resilient, collaborative, high-performing culture.

If this excites you, we'd love to meet you.

You must be work authorized in the United States without the need for employer sponsorship.

• Lead the team defining and evolving Ridgeline's Semantic Layer — setting the direction for data contract adoption across product engineering so that schema validation and enforcement become standard practice from the ground up
• Drive your team's roadmap toward a universal query interface — reducing direct-to-persistence-store patterns in product code and establishing store access adapters as the platform standard
• Partner with Staff+ engineers to shape the write path architecture, guiding replication and indexing pipelines toward a declarative, independently authored model running on shared compute infrastructure
• Ensure the data governance layer is reliable and well-owned — schema validation and audit lineage treated as first-class infrastructure, not an afterthought
• Champion the long-term investment in query federation — building organizational and technical readiness for cross-store analytics without coupling product engineering to persistence infrastructure
• Hire, develop, and retain top engineering talent — cultivating a culture of data correctness, technical thoroughness, and platform ownership
• Collaborate with product and engineering leadership to align data platform investments with company objectives
• Manage the inter-team interface with infrastructure partners — your team authors what flows through the persistence and event infrastructure; you own the contracts and access patterns that make that work reliable

• 10+ years of software engineering experience with at least 5+ years managing engineering teams
• Technical grounding in data systems — schema design, metadata infrastructure, query planning and execution, and data access patterns; you don't write production code daily, but you can engage credibly in architecture discussions, recognize tradeoffs in schema evolution and query interface design, and ask the questions that surface the tradeoffs others might skip past
• Experience building or managing data access abstractions — store access adapters, query federation engines, or platform-level query interfaces that standardize how services read data
• Familiarity with schema registry or metadata systems such as Confluent Schema Registry, Apache Atlas, DataHub, or equivalent data contract tooling
• Experience managing data write path infrastructure — replication pipelines, ETL/ELT systems, or data materialization services that feed downstream persistence stores
• Demonstrated ability to guide cross-team initiatives and influence without direct authority
• Experience operating high-availability systems with strict reliability and performance requirements
• Excellent communication skills and a passion for mentoring engineers and technical leaders
• Willingness to deepen expertise in the investment management domain and apply cutting-edge tools — including AI tools like GitHub Copilot — to accelerate development velocity and architectural clarity
• Strong problem-solving skills and a genuine interest in having fun at work

• Background in data governance frameworks in regulated environments
• Familiarity with change data capture technologies and event-driven architectures
• Experience in fintech, investment management, or other regulated industries

Ridgeline is the first front-to-back system of record for investment managers. Founded by visionary entrepreneur Dave Duffield (co-founder of both PeopleSoft and Workday), the company was created to modernize an industry held back by outdated, disconnected technology. Powered by a single, real-time data set and embedded AI, Ridgeline helps firms automate complexity, accelerate collaboration, and deliver tailored client experiences at scale — without added headcount or risk. Ridgeline is headquartered in Lake Tahoe, with offices in New York, Reno, and the Bay Area, and is recognized by Fast Company as a "Best Workplace for Innovators," by Frost & Sullivan as a "Technology Innovation Leader," and by The Software Report as a "Top 100 Software Company."

Ridgeline is proud to be a community-minded, discrimination-free equal opportunity workplace.

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