Data Engineer - Enterprise Data Platform & Lakehouse

UN Secretariat

New York (NY)

On-site

USD 120,000 - 180,000

Full time

7 days ago
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Job summary

The United Nations Joint Staff Pension Fund (UNJSPF) Office of Investment Management in New York seeks a Data Engineer to design and implement data infrastructure, build pipelines, and integrate diverse sources into the enterprise data platform and lakehouse.

The role requires 5+ years in data engineering, strong SQL and Python, cloud platforms, DevOps, data governance, and collaboration with investment, risk, analytics, and technology teams. Desirable Snowflake/Databricks; AI-assisted tools.

Qualifications

  • Advanced degree in a quantitative field required.
  • Bachelor's with two additional years of qualifying experience may be accepted.
  • Cloud data platform certification desirable.
  • Five+ years of progressive data engineering experience building pipelines on cloud platforms.

Responsibilities

  • Design and develop data solutions and infrastructure addressing technical problems with stakeholders.
  • Build, test, deploy, operate, and enhance production data pipelines and platform components.
  • Apply SDLC and DevOps practices to ensure reliable data products.
  • Implement data governance, protection, privacy, and security requirements.
  • Create and maintain comprehensive technical documentation.

Skills

SQL
Python
ETL/ELT
Cloud Platforms
Data Modeling
DevOps
Documentation
Communication
Agile
AI Tools

Education

Master's degree in quantitative field
Bachelor's degree + 2 years experience
Cloud data platform certification desirable

Tools

Snowflake
Databricks
AWS
Azure

Job description

The United Nations Joint Staff Pension Fund (UNJSPF) Office of Investment Management in New York seeks a Data Engineer to design and implement data infrastructure, build pipelines, and integrate diverse sources into the enterprise data platform and lakehouse.

The role requires 5+ years in data engineering, strong SQL and Python, cloud platforms, DevOps, data governance, and collaboration with investment, risk, analytics, and technology teams. Desirable Snowflake/Databricks; AI-assisted tools.

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