Senior Engineer – Ontology Platform

SS&C Technologies

. Join the Ontology Platform team and report to the Ontology Platform Lead .

Posted 9/23/2026full-timeRemote • United StatesSenior💰 $165,000 - $175,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data modeling, ETL/ELT processes, and building data pipelines while ensuring data quality and performance. Proficient in translating business requirements into technical structures and supporting production operations with a focus on operational excellence.

Highest-signal resume keywords

Data ModelingETL/ELT PatternsSQLAI Coding AgentsProduction Operations

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data PipelinesData QualityValidation LogicReconciliation LogicSchema HandlingData TransformationMonitoringIncident ResponseTroubleshootingDocumentation

Soft Skills

CommunicationCollaborationProblem-Solving

Tools & Technologies

AirflowSparkKafkaIcebergTrinoRDFOWLSPARQL

Industry Keywords

OntologyKnowledge GraphMaster Data ManagementFinancial Services Data

Tech Stack

Tools & technologies

AirflowETLKafkaSDLCSparkSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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