Senior Data Engineer - Data and Platforms

at  Houseful

Hybrid - Minimum 2 days on site in London, Tower Bridge HQ
At Houseful, we’re here to help everyone make intelligent decisions about their home
Do the best work of your life!
We make moves with head and heart to achieve our big ambitions, and to drive progress in the property market. There’s never been a better time to join us.
Houseful is home to trusted brands Zoopla, Alto, Hometrack, Calcasa, Mojo and Prime location. Together were creating the connections that power better property decisions, by unlocking the combined strength of software, data and insight.
Located within the Homes business unit of Houseful, Zoopla is one of the most recognised and loved UK consumer property brands. Our mission is to connect everyone to their home and give them better choices around it, whether moving, managing or financing. Over 60 million people visit Zoopla every month to access comprehensive data and information on every UK property, search over 500,000 homes for sale and rent, find the best agents and secure the latest mortgage deals. Zoopla is part of Houseful, the leader in residential property software, data and insight, and is sister brand to Hometrack, Alto and Mojo among others.
At Zoopla we know what a home is really worth, but more importantly we know how it should make you feel. Since 2008 we’ve been helping to make a house a home, and supporting you every step of the way. Our market-leading data means we’ve always got our finger on the pulse, and you’ll want to be a part of it! We want to help everyone make intelligent home buying decisions. We are building a team that will have the once in a career opportunity to re-imagine an industry.
We need a Senior Data Engineer to join our Homes data platform team and help us build our next generation data platform and pipelines, and inspire best practice for data within Zoopla.

As a Senior Data Engineer at Houseful you will:

• Lead and mentor junior data engineers by demonstrating excellent technical knowledge and fostering their growth within the organisation
• Architect and build scalable ETL/ELT pipelines to process large volumes of data from various sources using AWS technologies.
• Drive and develop the data warehousing solutions utilising Amazon Redshift, Databricks, or similar data warehousing/data lakehouse technologies, ensuring they align with business goals
• Collaborate strategically with software engineers, data analysts and data scientists to ensure data availability and quality for model training and evaluation, promoting MLOps across the organisation
• Identify and address performance bottlenecks in data pipelines and queries to ensure high efficiency and reliability.
• Establishing and maintaining monitoring and alerting systems to proactively manage data infrastructure health and performance.
• Maintain comprehensive documentation for data systems, processes, and workflows.
• Champion and implement data engineering best practices, including data governance and data security.

Essential skills:

• Proficiency in Python, SQL (understanding of Spark and DBT is a bonus)
• Strong experience with AWS services such as AWS Lambda, S3, AWS Redshift, AWS Glue (databricks knowledge is an additional plus)
• Experience building out data warehouses and building data pipelines
• Extensive knowledge on SQL, NoSQL databases
• Terraform, or similar IaC (Infrastructure as Code) platform
• Experience with Orchestration tools (e.g. AWS Step Functions, Airflow)

Desirable:

• Experience understanding and deploying machine learning models in production environments

Please refer the Job description for details