Front-Office Analytics Engineer - AI Tools & Dashboards

Cleartech Recruiting; New York (NY); On-site; USD 120,000 - 190,000; Full time

Job summary

Cleartech Recruiting's client in the investment space seeks an Analytics Engineer to design and ship data, analytics, and AI-enabled tools used by portfolio teams to monitor risk and evaluate opportunities.

You will build models, pipelines, and dashboards with Python, SQL, and Spark on modern data platforms, collaborating with portfolio managers and analysts to translate requirements into production-grade solutions.

Qualifications

• 3–5 years as a software, data, or analytics engineer, ideally supporting front-office users in financial services.
• Strong Python data skills with Pandas and NumPy; advanced SQL with relational modeling.
• Experience shipping user-facing analytics via BI tools or Python web frameworks; familiarity with AI-assisted development.

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.

Skills

Python data skills

Pandas & NumPy

Advanced SQL

Spark-based platforms

AI-assisted development

Tools

Spark-based platforms

Databricks

Snowflake

Job description

Cleartech Recruiting's client in the investment space seeks an Analytics Engineer to design and ship data, analytics, and AI-enabled tools used by portfolio teams to monitor risk and evaluate opportunities.

You will build models, pipelines, and dashboards with Python, SQL, and Spark on modern data platforms, collaborating with portfolio managers and analysts to translate requirements into production-grade solutions.