Data Engineer (Python, PySpark, Azure/AWS) (CPT)

ENVIRONMENT:

PLAY a key role in delivering trusted data products that enable investment, operational, and client-facing decision-making across an innovative Investment Management firm seeking a skilled, curious, and passionate Data Engineer. You will help drive the evolution of the enterprise data platform in this hands-on where you will work with structured and unstructured data, implement robust data pipelines, and contribute to data quality, governance, and observability practices that ensure confidence in the firm’s data products. The role will suit an Engineer with experience designing, building, and operating modern data platforms in production environments. You will require a Degree in Computer Science/Engineering/Maths or related quantitative field, 4 years suitable experience including strong Python, PySpark, Azure/AWS or GCP and experience utilising Azure Pipelines, GitHub Actions, or Jenkins.

DUTIES:

· Own data products from ingestion through to trusted consumption, ensuring data is reliable, accessible, and fit for purpose.

· Design, build, and operate scalable ELT and ETL pipelines across structured and unstructured data sources.

· Develop and maintain modern cloud-based data platforms using industry-standard Engineering practices and tooling.

· Implement data quality, governance, and observability capabilities to ensure trust in data products.

· Deliver data solutions through CI/CD pipelines and Infrastructure-as-Code, contributing to a robust and maintainable Engineering ecosystem.

· Evaluate and apply emerging technologies, including AI and LLM-based tooling, to improve Engineering productivity and business outcomes.

REQUIREMENTS:

Qualifications –

· Degree in Computer Science, Engineering, Mathematics, Science, or a related quantitative field.

Experience/Skills –

· At least 4 years of experience building, deploying, and operating data pipelines in production environments.

· Strong Python and PySpark skills, with a solid understanding of modern Data Engineering practices.

· Hands-on experience with a major cloud platform such as Azure, AWS, or GCP.

· Experience building and maintaining CI/CD pipelines using tools such as Azure Pipelines, GitHub Actions, or Jenkins.

ATTRIBUTES:

· The ability to build and maintain meaningful relationships.

· Able to ‘approach and own’ and continuously looks for opportunities to develop.

· A strong belief in doing the right thing.

· Can recognise and embrace change.