Senior Data Engineer

Zoopla

. Own Data Engineering projects end to end, from technical direction to business impact .

Posted 10/15/2026full-timeLondon • United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and managing production data pipelines, with a strong focus on data governance, ingestion patterns, and the application of AI tools in engineering. Proficient in Python, SQL, and modern lakehouse technologies, ensuring effective collaboration with platform engineers and mentoring of team members.

Highest-signal resume keywords

PythonSQLDatabricksAWSData Governance

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Hard Skills

Data Pipeline DevelopmentData Ingestion PatternsInfrastructure as CodeChange Data CaptureEvent-Driven IngestionStreaming IngestionData QualityPersonal Data HandlingCode ReviewMentoring

Soft Skills

CommunicationCollaborationProblem-Solving

Tools & Technologies

TerraformDbtFivetranRudderStackDatabricks LakeflowAuto LoaderDelta SharingModel Context Protocol

Industry Keywords

Data EngineeringData GovernanceSoftware FactoryProduction SystemsConsumer Businesses

Tech Stack

Tools & technologies

AWSETLPythonSQLTerraformUnity

About the role

Key responsibilities & impact

Own Data Engineering projects end to end, from technical direction to business impact
Design and build standard data ingestion and export patterns
Move existing pipelines onto standard patterns
Build governance into every pipeline, including access, personal data, lineage and cost
Use AI to make data engineering patterns faster to apply
Help bring Data Engineering into the software factory
Review code, mentor other engineers and share knowledge
Take responsibility for keeping production systems healthy
Work closely with platform engineers to align technical systems and make ambitious choices
Report to the Data Engineering Manager

Requirements

What you’ll need

Substantial experience building and running production data pipelines that other teams and customers depend on
Strong Python and SQL
Deep experience with a modern lakehouse, ideally Databricks and Unity Catalog, and with dbt
Comfortable on AWS and with infrastructure as code (Terraform)
Strong grounding in ingestion and integration patterns, including managed connectors, change data capture, event-driven and streaming ingestion, and exports to external systems and customers
Track record of simplifying one-off pipelines into a small number of patterns without breaking existing systems
Experience using AI tools in engineering work, with a clear view on where they help and how to keep them safe
Practical data governance experience, including access control, data quality and personal data handling
Ability to explain technical concepts in plain English and push back when the request does not match the problem
Nice to have: Fivetran, RudderStack or similar ingestion and reverse ETL tools
Nice to have: Databricks Lakeflow, Auto Loader or Delta Sharing
Nice to have: exposure to Model Context Protocol (MCP) servers or similar agent tooling
Nice to have: experience in property, marketplaces or other data-rich consumer businesses

Benefits

Comp & perks

Hybrid setup with 3 days each week in the Tower Bridge office and remote work at home for 2 days per week
25 days annual leave plus additional leave benefits, including extra days for length of service and other leave perks
Cycle to work scheme
Electric car scheme
Free Calm App membership
Enhanced parental leave
Fertility treatment financial support
Group Income Protection
Private medical insurance
On-site gym in London
7.5% company pension contribution
Discretionary annual bonus up to 10% of base salary