Data Engineer

Position: Data Engineer
Location: London, UK (Hybrid-3 days a week from office)
Long term position

Job Purpose

Strong technical engineering skills with a practical understanding of analytics, data modelling, testing, governance, and stakeholder collaboration.

Primary Objectives

1. Build and mature a modern, scalable data platform.
   Design and maintain a trusted, governed data warehouse environment.
2. Create high-quality single-source-of-truth data products for business teams.
3. Develop scalable analytics data models using Snowflake and dbt.
4. Improve data quality, reliability, lineage, and consistency across business domains.
5. Support business reporting and analytics through strong semantic layer and Tableau enablement.
6. Establish engineering best practices such as testing, documentation, CI/CD, code reviews, observability, and version control.
7. Partner with stakeholders, analysts, integration engineers, and platform teams to onboard and model new data sources.
8. Drive KPI standardization, metric consistency, and data governance across the organization.
9. Improve warehouse performance, scalability, maintainability, and trust in analytics outputs.

Key responsibilities

Design, build, and maintain scalable analytics data models within Snowflake and dbt

Develop and maintain trusted single-source-of-truth datasets and business-facing data products

Implement robust testing, documentation, and governance standards across the analytics layer

Collaborate with business analysts and stakeholders to understand reporting and analytics requirements

Work closely with integration engineers and platform teams to onboard and model new data sources

Manage and optimize ingestion/activation workflows using platforms such as Fivetran and Hightouch

Support Tableau semantic layer design and reporting performance optimization

Ensure data quality, lineage, consistency, and reliability across business domains

Contribute to data warehouse architecture, scalability, and performance improvements

Help establish engineering best practices including CI/CD, code reviews, observability, and version control

Support data governance initiatives including KPI standardization and metric consistency

Assist with data migrations, source onboarding, and modernization initiatives

Key Skills/Knowledge:

Experience in analytics engineering, data engineering, or modern BI engineering roles

Strong hands-on experience with Snowflake

Advanced dbt experience including modular modeling, testing, documentation, and deployments

Strong SQL skills with experience optimizing large-scale analytical workloads

Experience building dimensional models and business-friendly semantic layers

Experience with Tableau including supporting scalable reporting and dashboard development

Hands-on experience with ingestion and activation platforms such as Fivetran and Hightouch

Strong understanding of ELT pipelines, orchestration, and modern data stack architecture

Experience implementing data quality frameworks and automated testing

Familiarity with Git-based workflows and software engineering best practices

Tools and Technology Environment

• Snowflake
• dbt
• Tableau
• Fivetran
• Hightouch
• Modern ELT and cloud data warehouse tooling
• Git / CI-CD workflows

Experience required:

Essential

• 4+ years’ experience in analytics engineering, data engineering, or modern BI engineering roles
• Experience scaling greenfield or rapidly growing data warehouse environments
• Experience with customer data platforms, marketing data, or Salesforce ecosystems
• Exposure to orchestration tools such as Airflow or Dagster
• Experience designing governed metric layers and centralized KPI frameworks
• Experience with cloud-native data platform performance optimization and cost management
• Exposure to data observability or lineage tooling