Senior Engineering Manager, Ontology Platform

This is a fully remote position, open to applicants in New Jersey, +1 more state.

📋 Description

• Assemble, lead, and expand an initial team of 5-6 engineers.

• Recruit, oversee performance, facilitate career growth, and provide daily leadership.

• Define team structure, set priorities, and create a delivery roadmap in collaboration with product and business stakeholders.

• Cultivate engineering culture and practices, including code reviews, on-call rotations, delivery cadence, and technical documentation.

• Maintain a hands-on role in architecture, code reviews, and the implementation of essential components.

• Represent the team and platform roadmap to senior stakeholders.

• Establish and exemplify agentic SDLC adoption utilizing AI coding agents.

• Oversee the architecture for services, APIs, and data pipelines that ingest source-system data and apply ontology mappings.

• Make informed technical decisions regarding graph databases, relational stores, schema/graph modeling, indexing, and performance optimization.

• Provide guidance on configuration tools for mappings, rules, and exception handling.

• Guarantee production-quality ingestion connectors, transformation logic, validation engines, and break-detection pipelines.

• Implement version control, automated testing, CI/CD, and observability practices.

• Design adaptable configuration and integration points for new systems, domains, and rules.

• Define and refine the enterprise ontology, translating it into schemas, graph structures, or data contracts.

• Lead the mapping from source to ontology and reconcile conflicting system definitions.

• Direct rules and validation frameworks for identifying, triaging, and resolving data discrepancies.

• Leverage and enhance the foundational enterprise data platform.

• Collaborate with the data platform team on capability gaps, shared roadmaps, and design choices.

• Convert business, regulatory, governance, and compliance requirements into engineering and product decisions.

• Manage technical debt and drive platform evolution.

⛳️ Requirements

• 8-12 years of experience in software/data engineering, particularly in designing and constructing production-grade platforms or services.

• Previous experience as an Engineering Manager or in a similar role, with direct responsibility for managing engineers.

• Proficient in at least one modern backend programming language, such as Python, Java, Scala, or Go.

• Experience in API design, service architecture, and writing testable, maintainable production code.

• Background in designing and implementing data modeling/mapping frameworks.

• Hands-on experience with graph databases and/or semantic web standards like RDF, OWL, and SPARQL, or comparable modeling technologies.

• Experience in developing configurable, multi-tenant platforms or internal products.

• Strong database and data engineering competencies across relational and non-relational systems.

• Familiarity with data pipelines, ETL/ELT processes, and large-scale heterogeneous data sources.

• Experience with CI/CD, automated testing, infrastructure-as-code, and observability/monitoring practices.

• Experience building on a foundational/shared enterprise data platform.

• Excellent communication skills with business, compliance, and senior stakeholders.

• Practical hands-on experience using AI coding agents like Claude Code or GitHub Copilot as part of the core development workflow.

• Experience in financial services data environments is an advantage.

• Familiarity with enterprise ontology, knowledge graphs, or MDM platforms is preferred.

• Experience in scaling a small engineering team is a plus.

• Experience with cloud-native architectures and data platforms is desirable.

• Knowledge of data governance and metadata management tools is advantageous.

• A background in financial services, asset management, or another regulated, data-intensive industry is a plus.

🏝️ Benefits

• Medical, dental, and vision insurance coverage.

• 401(k) plan with company matching.

• Paid time off.

• Holidays.

• Parental leave.

• Opportunity for professional development reimbursement.

• Eligibility for discretionary annual bonuses.

• Eligibility for equity awards, including restricted stock units or stock options.