Data Engineer, Internal Audit Analytics | Associate

Goldman Sachs

Birmingham

On-site

GBP 70,000 - 100,000

Full time

14 days+

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Job summary

Goldman Sachs is seeking an Associate in Data Strategy and Analytics to design and implement production-grade data pipelines and data products for the Internal Audit division. You will source, transform and curate data, collaborating with audit teams and data owners to create reusable solutions that scale across audit coverage.

The role emphasizes Python, SQL, and data modelling skills, with exposure to Snowflake and cloud platforms.

Qualifications

  • 3+ years of relevant data engineering, software engineering or data-platform experience.
  • Bachelor’s degree or equivalent practical experience in computer science, engineering or a related quantitative discipline. A master’s degree is welcome.
  • Hands‑on proficiency in Python, including Pandas, Polars and PySpark, with experience writing testable and maintainable code.
  • Strong SQL proficiency and practical understanding of OLTP databases, relational design and query performance.
  • Strong understanding of data modelling, data warehousing, dimensional modelling and slowly changing dimensions.
  • Experience designing and implementing ETL/ELT pipelines and working with data‑lake, lakehouse or cloud data
  • Strong data analytics and problem‑solving skills, including the ability to profile, interpret and analyse data
  • Clear written and verbal communication and the ability to collaborate across technical and non‑technical teams.

Responsibilities

  • Design, build, test and support production-grade ETL/ELT pipelines that source, transform and curate data for Internal Audit.
  • Develop maintainable Python solutions using Pandas, Polars and PySpark, selecting fit-for-purpose approaches based on scale, performance and operational needs.
  • Write advanced SQL for data transformation, reconciliation, profiling and analysis across OLTP and analytical data platforms.
  • Design data models for operational and analytical use cases, including dimensional modelling, slowly changing dimensions, lakehouse and data-lake patterns.
  • Work with platforms such as Snowflake and relational databases including DB2 and PostgreSQL, applying sound principles for schema design, performance and data movement.
  • Implement data-quality checks, controls, lineage, observability, documentation and automated tests to improve trust and supportability.
  • Contribute to AI-ready data products and semantic layers that provide consistent business meaning and governed access to data.
  • Partner with audit teams and data owners to understand requirements, resolve data discrepancies and deliver reusable solutions.
  • Participate in design reviews, code reviews, version-control and CI/CD practices, and provide effective production support.
  • Communicate progress, issues and technical decisions clearly to both technical and non-technical stakeholders.

Skills

Python
Pandas
Polars
PySpark
SQL
Data modelling
ETL/ELT pipelines
Cloud data services
Data warehousing
Stakeholder communication

Education

Bachelor’s degree or equivalent practical experience in CS, engineering or related quantitative discipline
Master’s degree welcome

Tools

Snowflake
DB2
PostgreSQL
Spark
CI/CD
Containers
Cloud platforms (AWS/Azure/GCP)

Job description

Goldman Sachs is seeking an Associate in Data Strategy and Analytics to design and implement production-grade data pipelines and data products for the Internal Audit division. You will source, transform and curate data, collaborating with audit teams and data owners to create reusable solutions that scale across audit coverage.

The role emphasizes Python, SQL, and data modelling skills, with exposure to Snowflake and cloud platforms.

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