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# Data Engineer

- **Company:** Zinc
- **Location:** London, UK
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Software as a Service, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Warehousing, PostgreSQL, MongoDB, Standard Sql, SQL Databases, Scripting, AWS Lambda, Git, Information Technology, Software Version Control, Data Pipelines
- **Published:** May 22, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=7654bccd9c41970f

## About the Role

Do you have experience in Scripting?, * Strong SQL and PostgreSQL skills

 * Experience with Airbyte or a similar ETL/ELT tool (e.g. Fivetran, Stitch)
 * AWS experience - Lambda and S3 at minimum
 * Git / version control
 * 2-3 years in a data engineering role, ideally at a SaaS or tech company

Desirable:

 * MongoDB experience (our upstream source data)
 * dbt for data transformation
 * Python scripting
 * Experience at a scaling start-up

## Description

We're looking for a Data Engineer to join our Technology team. Our data warehouse infrastructure is growing fast, and we need someone to own the pipelines that power our ops team.
This is a pure engineering role. You'll be building and maintaining the systems that move, transform, and serve data across the business. If you want to work on analytics or BI, this isn't the role for you. If you want to build robust pipelines and warehouse infrastructure at a fast-moving, AI-native SaaS company, read on.

You'll thrive here if you're self-directed, enjoy owning a problem end-to-end, and can communicate clearly with non-technical stakeholders. We're a small team and you'll have real impact from day one., *
Build and maintain ETL/ELT pipelines using Airbyte

 * Manage and optimise our PostgreSQL data warehouse
 * Write and optimise SQL for internal ops team consumption
 * Work with AWS Lambda and S3 for pipeline orchestration
 * Translate business requirements into data pipeline solutions
 * Support infrastructure reliability across the tech stack


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