Job Description

Our client in the investment space is looking for an Analytics Engineer to help design and ship the data, analytics, and AI-enabled tools that investment professionals rely on to monitor portfolios, manage risk, and evaluate opportunities.

Responsibilities:

• Build and maintain analytics, calculations, and models covering portfolio monitoring, risk, and performance.
• Engineer data pipelines and data models in Python, SQL, and Spark-based platforms.
• Deliver dashboards, APIs, and AI-powered tools that let investment users explore data and run scenarios.
• Meet directly with portfolio managers and analysts to gather requirements and validate prototypes.
• Help newly launched investment teams get the data and tooling they need from day one.
• Partner with data engineering, market data, governance, and platform teams to keep solutions reliable and secure in production.

Required Experience:

• Roughly 3 to 5 years as a software, data, or analytics engineer, ideally supporting front-office users in financial services.
• Strong Python data skills (Pandas, NumPy, notebooks, plotting libraries) and advanced SQL with relational modeling.
• Exposure to a distributed data platform such as Spark, Databricks, or Snowflake.
• Working knowledge of at least one asset class, such as equities, credit, or fixed income.
• Experience shipping user-facing analytics through a BI tool or Python web framework, plus familiarity with AI-assisted development.