Senior Analytics Engineer, Data Modelling & Governance

Contract: Full-time contractor

Location: remote within EU time zones

Language: English

Start Date: ASAP

About the Role

A leading product-led technology company is evolving its data operating model from a

centralised data platform to a federated, domain-oriented ecosystem built around a modern

Data Platform as a Service (DPaaS) and standardised Medallion architecture.

This role sits within the central data function and focuses on Silver-layer data modelling

and data governance. You will build governed, reusable data assets while helping

engineering teams adopt the new platform and operate independently within established

standards.

Your Mission

You will act as the bridge between systems producing data and the teams consuming it.

Your responsibilities will cover:

1. 2. Building and maintaining the Silver layer — modelling system data into governed,

reusable assets that provide a Single Source of Truth.

Data modelling and governance enablement — acting as the subject matter expert,

supporting engineering teams with modelling standards, governance and best

practices.

What You'll Do

• Define Silver-layer modelling standards and build reference models using dbt.

• Translate source-system data into clean, documented and reusable domain assets.

• Support migration from a legacy data platform to DPaaS, including hands-on

migration work where required.

• Establish technical guardrails covering data contracts, naming conventions,

lineage, metadata and testing.

• Work closely with Product and Engineering teams to adopt the new platform and

modelling standards.

• Review designs, document reusable patterns and remove technical blockers.

• Champion data governance principles across engineering domains.

• Develop reusable patterns, best practices and enablement materials for the wider data

organisation.

Technical Requirements

• Advanced, hands-on dbt experience.• Strong knowledge of data modelling, including dimensional, analytical and reusable

domain models.

• Advanced SQL, including complex transformations, querying and optimisation.

• Experience with Snowflake or an equivalent cloud data warehouse, including

performance and cost optimisation.

• Strong data engineering fundamentals, including Airflow/orchestration, Git, CI/CD,

data ingestion and end-to-end pipelines.

• Practical experience with data governance, including data contracts, lineage,

metadata/cataloguing, data quality and testing.

• Understanding of Medallion or layered data architectures.

Soft Skills

• Strong ownership and proactive approach.

• Ability to influence teams and establish standards without formal authority.

• Clear communication with engineering, product and analytics stakeholders.

• Comfortable coaching and enabling other teams to become autonomous.

• Pragmatic approach to balancing quality with delivery speed.

• Comfortable working in an evolving and ambiguous environment.

Experience

• Senior-level experience in Analytics Engineering and/or Data Engineering,

typically 8+ years.

• Proven experience delivering production-grade data models.

• Degree in Computer Science, Engineering, Mathematics or a related discipline, or

equivalent practical experience.

• Experience within a fast-moving, product-led data organisation is advantageous.

• Experience supporting domain-oriented data ownership or similar data operating

model transformations is advantageous.