Job Purpose

This role sits at the intersection of financial data engineering and fixed income domain expertise. The incumbent will complete a structured three-month onboarding program, progressing from supervised document parsing and data validation to independent ownership of securities with standard structures. Training benchmarks include competency assessments, accuracy thresholds, and throughput targets.

The training curriculum for the Data Engineer contains high level overviews of the complex structures worked on by more senior personnel as well as reference data client use cases so that the incumbent can differentiate between legal and financial language that is relevant to and required by our client base versus jargon describing information that is not required and, so that the incumbent can identify new financing techniques that come to market. The incumbent must then apply this foundation of knowledge via a logical sequence of decision-making events to determine relevancy of said information to our clients for any of their use cases and if deemed relevant, determine the appropriate next steps to ensure high client satisfaction levels.

The fixed income market consists of over two million active securities and the reference data provided by ICE Data Services for said securities is used by our clients to make trading decisions, settle trades, make investment decisions, manage portfolios, analyse risk, create security master files, create client statements and conduct other back office functions. Our reference data is also used by internal stakeholders such as the Evaluated Pricing, Index and Analytics groups said reference data plays an integral role in determining evaluated prices, determining whether or not a security should be added to or deleted from an index or indices, the weighted average of a security within an index and, performing a series of analytical calculations that are used both internally within Intercontinental Exchange (ICE) and externally by these stakeholder’s clientele.

Responsibilities

• Data Extraction & Transformation
  • Parse, interpret, and transform structured and unstructured data from legal prospectuses, offering circulars, regulatory filings, trustee reports, and vendor feeds into normalized reference data fields
  • Identify and handle edge cases, ambiguous legal language, and novel instrument structures using rule-based and judgment-driven approaches
• Data Quality & Governance
  • Execute multi-layer validation checks (completeness, consistency, business-rule conformance) to meet accuracy and timeliness SLAs
  • Investigate root causes of data anomalies and contribute to error taxonomy and resolution playbooks
  • Monitor data pipelines for drift, gaps, and outliers; escalate systematic issues with supporting evidence
• Client & Stakeholder Support
  • Respond to client data inquiries with structured, well-reasoned written responses — including restatement of the issue, methodology applied, and resolution rationale
  • Collaborate with internal consumers (Evaluated Pricing, Index, Analytics) to clarify reference data requirements and surface upstream data gaps
  • Serve as a subject matter escalation point for less experienced analysts on data interpretation questions
• Research & Document Procurement
  • Conduct targeted research and direct outreach to issuers, underwriters and trustees, to source authoritative documentation
  • Maintain sourcing audit trails and documentation metadata to support reproducibility and compliance requirements
• Process Improvement & Analytics
  • Identify workflow inefficiencies and propose automation or process redesign opportunities with quantified impact estimates
  • Build script-driven tools to accelerate repetitive data extraction and validation tasks
  • Contribute to ad hoc analytical projects including data quality dashboards, trend analyses, and executive reporting

Knowledge and Experience

• Bachelor’s degree in finance, Economics, Computer Science, Mathematics, or a related quantitative discipline
• Advanced Excel skills, including the use of complex formulas and pivot tables
• Working knowledge of Python, SQL, or similar tools for data manipulation and automation
• Familiarity with the use of AI tools to support data processing, analysis, and automation
• Proven ability to extract meaningful insights from dense legal and financial documents
• Strong written communication skills, with experience producing client- or stakeholder-facing documentation
• Fluency in English and a Nordics Language, further language proficiency is an advantage
• Excellent attention to detail, with a demonstrated ability to work accurately under time pressure

Preferred Knowledge and Experience

• Experience in fixed income operations, reference data, market data, or financial data management
• Exposure to fixed income instruments: bonds, structured products, municipals, ABS/MBS, convertibles
• Understanding of data governance frameworks, data lineage, or master data management concepts