Data Engineer, Investment Data Platform

The role

You will build and maintain data pipelines and transformations to create a unified data foundation for a prominent asset allocator. You will model investment and operational data and deliver datasets and reports to analysts and investment teams.

What you will do

• Build and maintain data pipelines and transformations in SQL and Python, using dbt, Snowflake, and orchestration tools such as Dagster, Airflow, or Azure Data Factory.
• Model investment and operational data so it is accurate and easy to use.
• Write tests, data quality checks, and reconciliations.
• Ship through code review and CI/CD.
• Help keep production pipelines monitored and reliable.
• Work with analysts and investment teams to understand what they need.
• Deliver datasets and reports including Power BI.
• Use AI-assisted development tools to work faster.

Required qualifications

• 3 to 5 years of hands-on experience in data engineering, analytics engineering, or a closely related software role.
• Strong SQL and Python, and solid grounding in data modeling and ETL/ELT.
• Experience with a modern data warehouse (Snowflake, Synapse, Databricks, or similar) and a transformation or orchestration tool (dbt, ADF, Airflow, Dagster, or similar).
• Habits of a careful engineer: version control, code review, testing, and monitoring.
• Strong analytical ability and attention to detail.

Nice to have

• Exposure to financial, investment, or private equity data.
• Azure data services, Azure DevOps pipelines, or Power BI.
• Experience reconciling data across systems.

About the company

Castleton Tower is a boutique consulting firm founded by executives who have built and led quantitative research, data science, and technology teams at top-tier hedge funds and asset managers. They work exclusively with investment management firms to modernize data infrastructure and build AI-ready foundations.