Senior Engineer – Ontology Platform

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

📋 Description

• Become a member of the Ontology Platform team and report directly to the Ontology Platform Lead.

• Oversee the ontology model and convert business ontology definitions into tangible, implementable platform structures.

• Detect overlapping or conflicting definitions among business teams and facilitate the pursuit of a unified, canonical perspective.

• Create and implement rules and validation logic to identify inconsistencies between source data and ontology expectations.

• Develop and manage reconciliation logic that compares data from source systems against the canonical ontology, highlighting exceptions for business-user resolution.

• Keep documentation updated regarding ontology structures, mapping conventions, and rule logic.

• Develop and sustain ingestion connectors for new source systems.

• Contribute to platform services and APIs that aid in mapping, configuration, and rules management.

• Utilize the foundational data platform's ingestion, storage, and computing capabilities.

• Advocate for an agentic SDLC approach using AI coding agents and associated tools.

• Design and maintain data models, schemas, and pipelines for ontology-mapped data.

• Create and enhance ETL/ELT transformations through processes like cleansing, harmonization, and canonical mapping.

• Ensure data quality, lineage, and performance throughout the pipeline.

• Oversee the complete onboarding of new data sources and business use cases through their production deployment.

• Support production operations, including monitoring, incident response, troubleshooting, and resolving data or pipeline issues.

• Develop and maintain runbooks, dashboards, and operational documentation.

• Collaborate directly with business users during onboarding to clarify mapping outcomes, discrepancies, and platform configuration tools.

⛳️ Requirements

• 5-9 years of experience in software/data engineering, including familiarity with data modeling, data pipelines, and production support for a data platform or similar systems.

• Proficient in managing the entire lifecycle of a feature or capability, from design discussions with business stakeholders through implementation, deployment, and continuous operational support.

• Strong foundation in data engineering fundamentals: SQL, ETL/ELT methodologies, data modeling (relational and/or graph), and experience in constructing or managing scalable data pipelines.

• Experience in building integrations or connectors to external/source systems, including addressing schema variations and data quality challenges at the source.

• Ability to convert ambiguous business requirements or definitions into precise technical structures and effectively communicate with both business stakeholders and engineers.

• Background in production operations: monitoring, incident response, and troubleshooting for data systems.

• Comfortable operating on a shared foundational data platform and addressing capability gaps instead of circumventing them.

• Practical, hands-on experience with AI coding agents like Claude Code, GitHub Copilot, or similar as integral components of the development workflow.

• Proven record of leveraging AI coding agents to significantly enhance delivery speed and quality.

• Experience in financial services data environments is advantageous.

• Prior exposure to ontology, knowledge graph, or master data management concepts would be beneficial.

• Familiarity with rules engines or validation/reconciliation frameworks would be a plus.

• Knowledge of graph databases or semantic web standards including RDF, OWL, and SPARQL would be valuable.

• Experience in onboarding new data sources or users onto a platform as a structured, documented process would be advantageous.

• Familiarity with foundational data platform technologies such as Airflow, Spark, Kafka, Iceberg, Trino, or similar would be beneficial.

• Experience mentoring others on the effective use of AI coding agents or agentic development workflows would be great.

🏝️ Benefits

• Medical, dental, and vision insurance coverage.

• 401(k) plan with company matching contributions.

• Paid time off.

• Observance of holidays.

• Parental leave.

• Opportunity for professional development reimbursement.

• Potential for an annual discretionary bonus.

• Possibility of equity awards, such as restricted stock units or stock options.