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Senior Analytics Engineer – Data Modelling & Governance

Signify Technology European Union
Remote
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AI Summary

Lead the transition to a federated data ecosystem by establishing Silver-layer data modelling standards and governance frameworks. Build and maintain governed, reusable data assets in dbt while coaching engineering teams on domain-oriented data ownership. Requires senior-level analytics engineering experience with advanced dbt, Snowflake, and data governance expertise.

Key Highlights
Centre of Excellence for Silver-layer data modelling and governance
Bridge between data-producing systems and consuming teams
Transition from centralized to federated domain-oriented data platform
Key Responsibilities
Set Silver-layer modelling standard and build reference models in dbt
Support migration from legacy data platform to modern DPaaS architecture
Establish and enforce standards covering data contracts, naming conventions, lineage, metadata and testing
Act as 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
Technical Skills Required
dbt Snowflake Advanced SQL
Benefits & Perks
Fully remote across Europe

Job Description


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:

  1. Build and maintain the Silver layer: Model source-system data into governed, reusable assets that act as a Single Source of Truth.
  2. 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.



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