Senior Analytics Engineer – Data Modelling & Governance
Contract type:
Contractor
Contract length:
12 months, extendable
Location:
Fully remote across Europe
About the role A leading product-led technology company is evolving its data operating model, moving from a centralised data platform towards a federated, domain-oriented ecosystem built around a modern Data Platform as a Service (DPaaS) and standardised Medallion architecture.
In the target model, ownership follows the teams that produce the data. Product & Engineering teams progressively own their data through to the Silver layer, while the central Data function owns the platform, standards and governance.
This role sits at the heart of that transition. You will act as the Centre of Excellence for Silver-layer data modelling and data governance, building the foundations for a highly discoverable data environment while enabling engineering teams to work autonomously.
Your mission
You will act as the bridge between the systems that produce data and the teams that consume it.
Your mission has two complementary sides:
Build and maintain the Silver layer:
Model source-system data into governed, reusable assets that act as a Single Source of Truth.
Drive modelling and governance standards:
Act as the subject-matter expert, guiding and coaching engineering teams so they can build their own domain data products using the right standards from day one.
What you’ll do
Set the Silver-layer modelling standard and build reference models in
dbt
.
Support migration from a legacy data platform to a modern
DPaaS architecture
.
Establish and enforce standards covering
data contracts, naming conventions, lineage, metadata and testing
.
Act as the technical consultant for engineering teams adopting the new data platform.
Champion data governance principles across engineering domains.
Develop repeatable patterns, best practices and enablement material for the wider data organisation.
What we’re looking for
Technical skills
Advanced, hands-on
dbt
experience.
Strong
data modelling
expertise, including dimensional and analytical modelling.
Advanced
SQL
, including complex transformations, querying and optimisation.
Strong experience with
Snowflake or an equivalent cloud data warehouse
.
Experience with
Airflow
, Git, CI/CD and end-to-end data pipelines.
Practical experience with
data governance
, including data contracts, lineage, metadata, data quality and testing.
Understanding of
Medallion / layered data architectures
.
Soft skills
Strong ownership and proactive approach.
Ability to influence teams and establish standards without formal authority.
Clear communication across engineering, product and analytics teams.
Ability to coach teams and make them self-sufficient.
Pragmatic approach to balancing technical quality with delivery.
Comfortable working within an evolving data environment.
Experience & qualifications
Senior-level experience, typically
8+ years
, in analytics engineering and/or data engineering.
Strong track record delivering production-grade data models.
Degree in Computer Science, Engineering, Mathematics or a related field, or equivalent practical experience.
Experience within a fast-moving, product-led data organisation is advantageous.
Experience supporting a transition towards
domain-oriented data ownership
is advantageous.