Data Engineer - Zoopla

Posted Yesterday
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London, Greater London, England
Software
The Role
Join Houseful as an Associate Data Engineer to build and maintain ETL/ELT pipelines, support data quality improvements, collaborate with cross-functional teams, monitor data pipelines, and follow best practices for data engineering.
Summary Generated by Built In

Description

Hybrid - Minimum 2 days on-site in London, Tower Bridge HQ

We’re hiring a mid-level Data Engineer for (a Houseful brand) to join our data platform team, help us build our next-generation data platform and pipelines, and inspire best practices for data within Zoopla.

As a Data Engineer at Zoopla, you will:

  • Design, build, and maintain ETL/ELT Pipelines, ensuring efficient data flow and transformation from various sources using AWS technologies and other tools.
  • Enhance Data Quality: implement robust validation checks, monitor data accuracy, and resolve inconsistencies. Proactively suggest improvements to data quality processes in collaboration with senior engineers.
  • Develop and Scale Data Warehousing Solutions: e.g., AWS Redshift, and Databricks, ensuring they align with evolving business requirements and scalability needs.
  • Collaborate Across Functions such as analytics engineers, software engineers, data analysts, and data scientists, ensuring timely and accurate data access for analytics, model training, and evaluation needs.
  • Monitor and Optimise Pipeline Performance, diagnosing and resolving bottlenecks. Work alone or with senior engineers to enhance system efficiency and responsiveness.
  • Implement Monitoring and Alerting Systems for data infrastructure health, enabling quick identification and response to potential issues.
  • Develop Documentation for data systems, workflows, and processes, ensuring clarity and accessibility for team members and stakeholders.
Requirements
  • Proficiency in Python and SQL for data manipulation and transformation. Familiarity with Spark and DBT is a plus.
  • Cloud Experience with AWS, data storage, processing, and orchestration services in cloud environments.
  • Data Pipeline Development and maintaining data pipelines or working with data warehouses, ensuring efficient data flow and reliability.
  • Experience with SQL and NoSQL Databases, enabling effective data storage solutions based on use cases.
  • Data warehousing and/or data lake experience.
  • Infrastructure as Code (IaC) such as Terraform with a willingness to expand expertise in infrastructure management and automation.

Interested? Let us know by applying to this role and we'll be in touch!

Benefits
  • An excellent base salary (more details via email / recruiter call)
  • Discretionary annual bonus up to 10% of base salary
  • Everyday Flex - greater flexibility over where and when you work
  • 25 days annual leave + extra days for years of service
  • Day off for volunteering & Digital detox day
  • Festive Closure - business closed for period between Christmas and New Year
  • Cycle to work and electric car schemes
  • Free Calm App membership
  • Enhanced Parental leave
  • Fertility Treatment Financial Support
  • Group Income Protection and private medical insurance
  • Gym on-site in London
  • 7.5% pension contribution by the company
  • Talent referral bonus up to £5K

Top Skills

AWS
SQL
The Company
HQ: London
737 Employees
On-site Workplace

What We Do

We’ve recently renamed our wider business to ‘Houseful’, which is why the name might be new to you. By doing so, we can now showcase the breadth of our brands and connected capabilities that are driving progress in the property industry.

Houseful is the leader in residential property software, data and insight - owning and operating a family of trusted and established brands, including Zoopla, Hometrack, Prime Location, Mojo, Alto and Calcasa.

It also means that when you work for one of our brands, you’re part of something much bigger. At Houseful, we are powering better property decisions for everyone - and our door is always open to new applicants, regardless of race, colour, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, or length of time spent unemployed.

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