[Hiring] Senior Engineering Manager, Ontology Platform @SS&C Technologies

Role Description

We are seeking a hands-on Senior Engineering Manager to build and lead a team (initially 5-6 engineers) responsible for architecting, building, and operating our enterprise ontology platform. This is a hands-on management role: you will manage and grow the team, set technical direction, and remain deeply hands-on in architecture and implementation decisions rather than operating purely at a planning/oversight level. You'll drive the build-out of a platform that ingests data from a wide variety of source systems, maps it to a canonical ontology, surfaces discrepancies ("breaks") between source data and ontology definitions, and gives business and technical users configurable tools to manage those mappings and exceptions, all in a financial services data environment where scale, correctness, and auditability matter.

The ontology solution is built on top of the enterprise's foundational data platform, so close partnership with that platform team is central to this role.

Qualifications

• 8-12 years of software/data engineering experience, including experience designing and building production-grade platforms or services (not primarily analytics/reporting work).
• Prior experience as an Engineering Manager or equivalent, with direct people-management responsibility (hiring, performance management, career development) for a team of engineers, not solely a tech-lead role without formal management authority.
• Strong software engineering fundamentals: proficient in at least one modern backend language (e.g., Python, Java, Scala, Go), API design, service architecture, and writing testable, maintainable production code, and comfortable staying hands-on despite management responsibilities.
• Demonstrated experience designing and implementing data modeling/mapping frameworks, ideally including ontology, knowledge graph, or master-data-style canonical models, and translating conceptual models into working schemas or graph structures.
• Practical experience with graph databases and/or semantic web standards (RDF, OWL, SPARQL) or equivalent experience with alternative modeling technologies.
• Experience building configurable, multi-tenant-style platforms or internal products where business users define behavior (rules, mappings, workflows) without engineering intervention.
• Solid database and data engineering skills across relational and non-relational systems, including experience with data pipelines, ETL/ELT, and handling large-scale, heterogeneous data sources.
• Experience with modern engineering practices: CI/CD, automated testing, infrastructure-as-code, observability/monitoring for production systems.
• Experience building on top of a shared/foundational enterprise data platform rather than a fully greenfield stack.
• Strong communication skills: able to work directly with business, compliance, and senior stakeholders.
• Experience in or working with financial services data environments is a plus.
• Practical, hands-on experience using AI coding agents as a core part of your development workflow.

Requirements

• Build, lead, and grow a team of 5-6 engineers, including hiring, performance management, career development, and day-to-day people leadership.
• Set team structure, priorities, and delivery roadmap in partnership with product/business stakeholders.
• Establish team engineering culture and practices: code review standards, on-call/support rotation, sprint or delivery cadence, and technical documentation habits.
• Stay hands-on: review and contribute to architecture, participate in code reviews, and step into implementation directly on critical or complex components.
• Represent the team and platform roadmap to senior stakeholders, translating engineering trade-offs and capacity into terms business leaders can act on.
• Own the core platform architecture: services, APIs, and data pipelines that ingest source-system data.
• Drive technical decisions on storage and query layers, including schema/graph modeling, indexing strategy, and performance tuning.
• Guide the build of the configuration layer of the product itself.
• Ensure the team ships production-quality code for core platform components.
• Establish engineering practices for the platform: version control, automated testing, CI/CD pipelines, and observability.
• Design for extensibility from day one; new source systems, new business domains, and new rule types should be addable through configuration.
• Define and evolve the enterprise ontology and translate that model into concrete schemas, graph structures, or data contracts.
• Lead the technical implementation of source-to-ontology mappings.
• Direct the design and implementation of the rules/validation framework.
• Leverage the capabilities of the enterprise's foundational data platform.
• Build synergies between the ontology platform and the foundational data platform.
• Proactively identify capability gaps and partner directly with the data platform team.
• Collaborate with the data platform team on shared roadmap items.
• Partner with business stakeholders, data governance, and compliance teams.
• Manage technical debt and platform evolution over time.

Benefits

• Medical, dental, and vision coverage.
• 401(k) plan with company match.
• Paid time off, holidays, and parental leave.
• Professional development reimbursement opportunity.
• Discretionary bonus and/or equity awards based upon individual and business performance.