Snowflake Data Engineer

Fractal | Intelligence For Imagination; City of Westminster; On-site; GBP 70,000 - 90,000; Full time

Job summary

Fractal | Intelligence For Imagination in the United Kingdom seeks a Snowflake Data Engineer to build and optimize data pipelines within Snowflake, including ML workloads. The role focuses on delivering month-long programme use cases from Pre-Prod to Prod.

You will work with Data Scientists to validate models, document findings, and support the PoC migration and warranty period, while promoting best practices in PySpark and SQL.

Qualifications

• Must have Snowflake experience including Snowflake ML.
• Experience building data models and pipelines in Snowflake.
• Proficiency in PySpark and SQL required.
• DBT experience is advantageous.
• Ability to collaborate with Data Scientists on PoC migrations.

Responsibilities

• Manage build of nominated Programme Use Cases within Client Snowflake (Pre-Prod).
• Support PoC migration phase with Data Scientists.
• Transform Programme PySpark pipelines for migration prep.
• Document performance and findings after models are built in Snowflake.
• Assist cutover of Snowflake models from Pre-Prod to Prod with Data Scientists.
• Provide warranty period support for issue tracking.

Skills

Snowflake experience

Snowflake ML

PySpark

SQL

DBT

Tools

Snowflake frameworks

Job description

• Must have Snowflake & / Snowflake ML experience - this is mandatory for this Fractal Engineer role.
• Fractal Data Engineer roles required with the necessary Snowflake experience.
• Data Build Tool (DBT) experience would be advantageous.
• To manage the build of nominated Programme Use Cases within Client Snowflake (Pre-Prod) during September 2026 through to December 2026 inclusive.
• Note : Exclusively for Programme Use Cases, the Fractal Engineers aligned to this area will be required to support the Data Scientists to run a Proof of Concept (PoC) Migration Phase.
• Support in transforming Programme PySpark for the respective use cases, as part of migration preparation.
• Work collaboratively with nominated Data Scientists (Programme) to validate the functionality / performance of the models.
• Document the performance, findings & observations, once the models have been built within Snowflake.
• Support the cutover of Snowflake built models from Pre-Prod to Prod, in collaboration with Data Scientists.
• Provide support during the Warranty Period for issue tracking / resolution.
• Role / Skills of the Snowflake Data Engineer for Programme Migrations
• Ideally competent to build data models / data pipelines with Snowflake ML, with input from the respective Data Scientists.
• Be able to leverage Snowflake frameworks & workflows to construct scalable models.
• Work collaboratively with the Data Scientists to ensure the newly built models in Snowflake function & perform correctly (when compared to the existing Programme use cases)
• It is important the resources work collaboratively with the nominated Data Scientists to help with model / data pipeline build standardisation, issue resolution, etc.
• PySpark experience. The pipeline is written in PySpark, it is vital that the engineers can quickly get up to speed on the pipeline, advise on efficiency improvements & best practise.
• SQL expertise.
• Snowflake experience alongside PySpark, so that they can advise if a better Snowflake-native solution exists - we are not tied to PySpark and are happy if there is a better solution for the pipeline.
  Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work® Institute and recognized as a 'Cool Vendor' and a 'Vendor to Watch' by Gartner.