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Abu Dhabi Investment Council (ADIC)

VP, Corporate Finance - Portfolio Analytics

Abu Dhabi Investment Council (ADIC)

Abu Dhabi, United Arab Emirates · Tempo pieno

Sii il primo a candidarti

Esperienza
8–12 anni
Stipendio
Aperture
1
Pubblicato
3 settimane fa
Modalità di lavoro
In ufficio
Istruzione
University degree in a relevant quantitative discipline
Requisiti di ammissibilità
Experienced professionals with a strong background in Python/SQL-based data engineering, quantitative development, or applied analytics in financial services or asset management.
Riprendere
È necessario candidarsi

Dove lavorerai

Descrizione del lavoro

Role overview

This position carries end-to-end technical and operational responsibility for ADIC’s proprietary liquidity model and the analytics tools that support it. The work is highly practical and centered on developing, improving, and maintaining production-ready code, creating and managing data pipelines, and connecting the firm’s data environment — including Snowflake, source platforms, FactSet, and internal databases — to the liquidity model.

The role also involves close collaboration with investment and support teams to produce dependable, repeatable analytics, reporting outputs, and one-off data extracts.

Education

  • A university degree in Computer Science, Software Engineering, Data Science, Financial Engineering, Quantitative Finance, Mathematics, or another related quantitative field is required.
  • Professional certifications in areas such as Snowflake or AWS/Azure Data Engineering, as well as finance credentials like CFA or CAIA, are advantageous but not mandatory.

Experience

  • Candidates should bring 8 to 12 years of practical experience in data engineering, quantitative development, or applied analytics.
  • At least 5 years of that background should include building and supporting production Python and SQL applications, along with data pipelines, within financial services or asset management.

Core focus

This is a hands-on technical leadership role with strong emphasis on engineering quality, reliability, and integration across financial data sources. The successful candidate will help ensure the liquidity model and related analytics run smoothly in a live environment and deliver consistent outputs for internal stakeholders.

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