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Data Engineer (MarkitEDM)

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Onsite

Data Engineer (MarkitEDM)

Signature IT World Inc

Data Engineer (MarkitEDM)

Skills

SQL QueriesData EngineeringSnowflakeData AnalysisAWSdbtApache AirflowAzure

19 days ago

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Important information


Contract type:

Freelance / Contract

Location:

New York, NY, USA

Work mode:

Onsite

Published on:

3 October 2026

What they need


Job Title: Data Engineer (MarkitEDM)

Location: New York City, NY / Chicago, IL

Job Type: Contract

Responsibilities:

  1. Design, develop, and maintain data mastering workflows using MarkitEDM or equivalent enterprise data management platforms
  2. Support end-to-end mastering logic for security reference data — including equities, fixed income, derivatives, and structured products — across multiple upstream vendor feeds
  3. Build and optimize data quality rules, survivorship logic, and golden record frameworks to ensure downstream data consumers receive clean, trusted data
  4. Integrate with industry data vendors (Bloomberg, ICE, etc.) and map vendor schemas to internal data models
  5. Troubleshoot production data issues, perform root cause analysis, and implement sustainable fixes with minimal business disruption
  6. Perform ad-hoc data analysis and communicate findings clearly to technical and non-technical stakeholders
  7. Collaborate with Data Governance, Front Office Technology, and Operations teams to define mastering rules, resolve data conflicts, and onboard new data domains
  8. Contribute actively to team objectives in a collaborative, outcomes-driven environment

Qualifications:

  1. 5+ years of experience in data engineering, data mastering or MDM-focused roles within financial services or asset management
  2. Hands-on experience with MarkitEDM or equivalent platforms
  3. Strong understanding of security reference and pricing data – including identifiers, corporate actions, asset classifications, and multi-vendor data sourcing
  4. Bachelor’s degree in Computer Science, Engineering, or a related field is required
  5. Proficiency in SQL, data modeling and ETL processes
  6. Familiarity with data quality frameworks, exception management workflows, and SLA-driven data operations
  7. Understanding of the financial services and asset management industry
  8. Ability to work collaboratively within a team-oriented environment
  9. Strong communication skills to engage effectively across technical and business teams
  10. Demonstrated ability to troubleshoot and solve technical challenges independently
  11. Exposure to cloud data platforms (Snowflake, Azure, AWS) or orchestration tools (Airflow, dbt) is a plus

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