Senior Engineering Manager, Ontology Platform

SS&C Technologies

. Build, lead, and grow an initial team of 5-6 engineers .

Posted 9/23/2026full-timeRemote • United StatesSenior💰 $185,000 - $195,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates extensive experience in software and data engineering, with a strong focus on architecture, API design, and data modeling. Proven ability to lead and grow engineering teams while ensuring high-quality production standards and effective collaboration with stakeholders.

Highest-signal resume keywords

Engineering ManagementAPI DesignData ModelingGraph DatabasesCI/CD Practices

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonJavaScalaGoData EngineeringETL/ELTAutomated TestingInfrastructure-as-CodeData PipelinesEnterprise Ontology

Soft Skills

Strong CommunicationPeople Leadership

Tools & Technologies

AI Coding AgentsGitHub CopilotClaude CodeObservability ToolsMetadata Management Tooling

Industry Keywords

Financial ServicesData GovernanceRegulated IndustryData-Intensive IndustryKnowledge Graph

Tech Stack

Tools & technologies

CloudETLJavaPythonScalaSDLCGo

About the role

Key responsibilities & impact

Build, lead, and grow an initial team of 5-6 engineers
Hire, manage performance, support career development, and provide day-to-day people leadership
Set team structure, priorities, and delivery roadmap with product and business stakeholders
Establish engineering culture and practices, including code reviews, on-call rotation, delivery cadence, and technical documentation
Remain hands-on in architecture, code reviews, and implementation of critical components
Represent the team and platform roadmap to senior stakeholders
Set and model agentic SDLC adoption using AI coding agents
Own architecture for services, APIs, and data pipelines ingesting source-system data and applying ontology mappings
Make technical decisions on graph databases, relational stores, schema/graph modeling, indexing, and performance
Guide configuration tools for mappings, rules, and exception handling
Ensure production-quality ingestion connectors, transformation logic, validation engines, and break-detection pipelines
Establish version control, automated testing, CI/CD, and observability practices
Design extensible configuration and integration points for new systems, domains, and rules
Define and evolve the enterprise ontology and translate it into schemas, graph structures, or data contracts
Lead source-to-ontology mappings and reconciliation of differing system definitions
Direct rules and validation frameworks for detecting, triaging, and resolving data breaks
Leverage and extend the foundational enterprise data platform
Partner with the data platform team on capability gaps, shared roadmaps, and design decisions
Translate business, regulatory, governance, and compliance requirements into engineering and product decisions
Manage technical debt and platform evolution

Requirements

What you’ll need

8-12 years of software/data engineering experience, including designing and building production-grade platforms or services
Prior experience as an Engineering Manager or equivalent, with direct people-management responsibility for engineers
Proficiency in at least one modern backend language, such as Python, Java, Scala, or Go
Experience with API design, service architecture, and testable, maintainable production code
Experience designing and implementing data modeling/mapping frameworks
Practical experience with graph databases and/or semantic web standards such as RDF, OWL, and SPARQL, or equivalent alternative modeling technologies
Experience building configurable, multi-tenant-style platforms or internal products
Solid database and data engineering skills across relational and non-relational systems
Experience with data pipelines, ETL/ELT, and large-scale heterogeneous data sources
Experience with CI/CD, automated testing, infrastructure-as-code, and observability/monitoring
Experience building on top of a shared/foundational enterprise data platform
Strong communication skills with business, compliance, and senior stakeholders
Practical hands-on experience using AI coding agents such as Claude Code or GitHub Copilot as a core development workflow
Experience in financial services data environments is a plus
Experience with enterprise ontology, knowledge graph, or MDM platforms is desirable
Experience growing a small engineering team is desirable
Experience with cloud-native architectures and data platforms is desirable
Familiarity with data governance and metadata management tooling is desirable
Background in financial services, asset management, or another regulated, data-intensive industry is desirable

Benefits

Comp & perks

Medical, dental, and vision coverage
401(k) plan with company match
Paid time off
Holidays
Parental leave
Professional development reimbursement opportunity
Eligibility for discretionary annual bonus
Eligibility for equity awards, such as restricted stock units or stock options