Data Engineer - Build AI-Ready Pipelines & Dashboards

Aries Global; Greater London; On-site; GBP 80,000 - 120,000; Full time

Job summary

Aries Global is seeking a data-focused professional to own the data foundations powering decision-making across the group and portfolio companies. You will design, build, and run pipelines and models using dbt and Snowflake, turning data into actionable dashboards and analyses for leadership and operators.

You will onboard new acquisitions, ensuring data enters the platform quickly and cleanly, and establish high standards for data quality and documentation to support AI-enabled products.

Qualifications

• Strong analytical foundations built through experience in start-ups, investment banking, PE/VC, strategy, or management consulting.
• Hands-on data skills with SQL and a modern data stack (dbt, Snowflake or similar); Python is a plus.
• Ability to thrive in ambiguity, form clear mental models quickly, take ownership, and dive deep into unfamiliar software domains.
• Clear communication in structured, concise, and compelling ways to explain data to non-technical people.

Responsibilities

• Own the data stack: design, build and run pipelines and models in dbt and Snowflake that are fast, tested and trusted.
• Turn data into decisions: build dashboards and portfolio reporting used by leadership and operators.
• Onboard new companies: bring acquisitions' data into the group platform quickly and cleanly.
• Make data AI-ready: set standards for quality and documentation that AI products depend on.

Skills

SQL

dbt

Snowflake

Python

Data storytelling

Tools

dbt

Snowflake

Job description

Aries Global is seeking a data-focused professional to own the data foundations powering decision-making across the group and portfolio companies. You will design, build, and run pipelines and models using dbt and Snowflake, turning data into actionable dashboards and analyses for leadership and operators.

You will onboard new acquisitions, ensuring data enters the platform quickly and cleanly, and establish high standards for data quality and documentation to support AI-enabled products.