Audit Data Engineer β€” Production-Grade Pipelines

Audit Data Engineer β€” Production-Grade Pipelines

Full-Time 63000 - 77000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Design and deploy data pipelines to support audit teams and deliver reliable data products.
  • Company: Goldman Sachs, a leading global investment banking firm.
  • Benefits: Competitive salary, comprehensive benefits, and opportunities for professional growth.
  • Other info: Collaborative culture with a focus on innovation and quality.
  • Why this job: Join a dynamic team and work on impactful data solutions in a prestigious environment.
  • Qualifications: Experience in Python, SQL, and a passion for data analytics.

The predicted salary is between 63000 - 77000 Β£ per year.

Goldman Sachs is seeking an Associate in Data Strategy and Analytics within Internal Audit.

You will design and deploy data pipelines and models to support third line assurance, collaborating with audit teams and data owners to deliver reliable, reusable data products.

You will build production-grade Python solutions, write SQL, and contribute to AI-ready data products while ensuring quality, documentation, and governance across data platforms.

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Audit Data Engineer β€” Production-Grade Pipelines employer: Goldman Sachs

Goldman Sachs is an exceptional employer, offering a dynamic work environment where innovation and collaboration thrive. With a strong commitment to employee growth, the firm provides extensive training and development opportunities, alongside a diverse and inclusive culture that values every individual's contributions. Located in a global financial hub, employees benefit from engaging with top-tier professionals while managing a portfolio of EMEA Corporate clients, ensuring meaningful and impactful work in the field of credit risk analysis.

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Contact Details:

Goldman Sachs Recruitment Team

We think you need these skills to ace Audit Data Engineer β€” Production-Grade Pipelines

Data Pipeline Design
Data Modelling
Python
SQL
Collaboration
Data Governance
Quality Assurance