Data Engineer

We're hiring a hands-on Data Engineer to join the Total Fund Management Portfolio Management Technology team. The role focuses on building and optimizing large-scale cloud data systems with Spark/PySpark and modern storage formats. KEY RESPONSIBILITIES Develop and optimize Spark workloads in cloud environments Work with large datasets using Parquet and Iceberg Translate requirements into robust engineering solutions Ensure performance, reliability, and maintainability Contribute to monitoring, documentation, and deployment MUST HAVE Strong Python and PySpark Hands-on Apache Spark, cloud preferred Databricks experience Large-scale data systems expertise Client-facing delivery background Independent problem-solving in ambiguous settings NICE TO HAVE AWS Glue and Lake Formation Airflow and orchestration tools Distributed data architectures Capital markets exposure

Develop and optimize large-scale cloud data systems and Spark workloads using Parquet and Iceberg. Ensure the performance, reliability, and maintainability of engineering solutions while contributing to monitoring and deployment.

Requires strong expertise in Python, PySpark, and Databricks for building large-scale data systems. Candidates should have a background in client-facing delivery and the ability to solve problems independently in ambiguous settings.

Identified from the job description. Confirm important requirements above.

• Python
• PySpark
• Apache Spark
• Databricks
• Parquet
• Iceberg
• AWS Glue
• Lake Formation
• Airflow
• Distributed Data Architectures
• Capital Markets
• Cloud Data Systems

• Data & Analytics
• Technology
• Engineering
• Finance & Accounting
• Software

Minimum experience

5+ years

Posting language

English

Working hours

40 hours per week