Senior Engineer – Ontology Platform

🔥 13 hours ago

🏖️ New Jersey, Massachusetts – Remote

🏖️ New Jersey – Remote 🍂 Massachusetts – Remote

💵 $165k - $175k / year

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 0%

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SS&C Technologies

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1986

💼 Consulting

🛡️ Insurance

📦 Logistics

Consulting • Insurance • Logistics

SS&C Technologies is a global leader in financial services and healthcare technology, recognized as the world’s largest independent hedge fund and private equity administrator, as well as the largest mutual fund transfer agency. The company offers a comprehensive range of solutions including asset management, banking, healthcare, insurance, and wealth management, leveraging proprietary software and extensive expertise to meet the operational needs of clients across multiple industries.

📋 Description

• Join the Ontology Platform team and report to the Ontology Platform Lead • Steward the ontology model and translate business ontology definitions into concrete, implementable platform structures • Identify overlapping or conflicting definitions across business teams and help drive toward a shared, canonical view • Design and build rules and validation logic to detect discrepancies between source data and ontology expectations • Build and maintain reconciliation logic comparing source system data against the canonical ontology and surface exceptions for business-user triage • Maintain documentation of ontology structures, mapping conventions, and rule logic • Build and maintain ingestion connectors for new source systems • Contribute to platform services and APIs supporting mapping, configuration, and rules management • Leverage the foundational data platform's ingestion, storage, and compute capabilities • Use and champion an agentic SDLC approach with AI coding agents and related tooling • Design and maintain data models, schemas, and pipelines for ontology-mapped data • Build and optimize ETL/ELT transformations through cleansing, harmonization, and canonical mapping • Ensure data quality, lineage, and performance across the pipeline • Own end-to-end onboarding of new data sources and business use cases through production deployment • Support production operations, including monitoring, incident response, troubleshooting, and resolving data or pipeline issues • Build and maintain runbooks, dashboards, and operational documentation • Work directly with business users during onboarding to explain mapping results, breaks, and platform configuration tools

🎯 Requirements

• 5-9 years of software/data engineering experience, including exposure to data modeling, data pipelines, and production support for a data platform or similar system • Comfortable working across the full lifecycle of a feature or capability, from design conversations with business stakeholders through implementation, deployment, and ongoing operational support • Solid data engineering fundamentals: SQL, ETL/ELT patterns, data modeling (relational and/or graph), and experience building or maintaining data pipelines at scale • Experience building integrations or connectors to external/source systems, including handling schema variation and data quality issues at the source • Ability to translate ambiguous business requirements or definitions into concrete technical structures and communicate clearly with business stakeholders and engineers • Experience with production operations: monitoring, incident response, and troubleshooting for data systems • Comfortable working on top of a shared foundational data platform and escalating capability gaps rather than building around them • Practical, hands-on experience using AI coding agents such as Claude Code, GitHub Copilot, or similar as a core part of the development workflow • Track record of using AI coding agents to meaningfully increase delivery speed and quality • Experience in or working with financial services data environments is a plus • Prior exposure to ontology, knowledge graph, or master data management concepts would be great • Experience with rules engines or validation/reconciliation frameworks would be great • Familiarity with graph databases or semantic web standards including RDF, OWL, and SPARQL would be great • Experience onboarding new data sources or users onto a platform as a repeatable, documented process would be great • Familiarity with Airflow, Spark, Kafka, Iceberg, Trino, or similar foundational data platform technologies would be great • Experience mentoring others on effective use of AI coding agents or agentic development workflows would be great

🏖️ Benefits

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