Remote Senior Data Engineer; Data Quality, PySpark, Databricks

Hi, we’re Smoove, part of the PEXA Group.

Our vision is to simplify and revolutionise the home moving and ownership experience for everyone. We are on a mission to deliver products and services that remove the pain, frustration, uncertainty, friction and stress that the current process creates.

We are a leading provider of tech in the property sector - founded in 2003, our product focus has been our conveyancer two-sided marketplace, connecting consumers with a range of quality conveyancers to choose from at competitive prices via our easy-to-use tech platform. We are now building out our ecosystem so consumers can benefit from our services either via their Estate Agent or their Mortgage Broker, through smarter conveyancing platforms, making the home buying or selling process easier, quicker, safer and more transparent

Why join Smoove?

Great question! We pride ourselves on attracting, developing and retaining a diverse range of people in an equally diverse range of roles and specialisms – who together achieve outstanding results. Our transparent approach and open-door policy make Smoove a great place to work and as our business expands, we are looking for ambitious, talented people to join us.

We are looking for a technically proficient Senior Data Engineer to join our growing Data team.

Your primary focus will be on ensuring data quality, stability, and reliability — from the moment data arrives in its rawest form to when it is used in decision-making dashboards and customer-facing reports.

You will optimise the transformation pipeline from start to finish, guaranteeing that datasets are robust, tested, secure, and business-ready.

Our data platform is built using Databricks, with data pipelines written in PySpark and orchestrated using Airflow. You will be expected to challenge and improve current transformations, ensuring they meet our performance, scalability, and data governance needs.

This includes work with complex, nested data structures, ensuring they are reliably parsed and transformed. Experience in managing sensitive data (PII) and implementing GDPR policies is required.

You’ll work closely with analysts, engineers, and business stakeholders to ensure that datasets are not only accurate but also trusted.

You will collaborate with product and engineering teams to incorporate data from new products into our core business datasets, ensuring that these new sources meet our data standards and are quickly usable for business intelligence.

You’ll help put controls in place — such as access policies, metadata layers, and automated data quality checks — to ensure long-term stability. Experience with a data governance platform like Alation is desirable.

While predominantly remote / home based the team meet up to 20-25 days per year for meaningful collaboration in either Leeds or Thame.

Key Responsibilities

• Ensure end-to-end data quality, from raw ingested data to business-ready datasets
• Optimise PySpark-based data transformation logic for performance and reliability
• Build scalable and maintainable pipelines in Databricks and Airflow
• Implement and uphold GDPR-compliant processes around PII data
• Collaborate with stakeholders to define what "business-ready" means, and confidently sign off datasets as fit for consumption
• Put testing strategies in place to detect data issues early and often
• Contribute to access management, metadata management, and wider data governance practices
• Help shape our approach to reliable data delivery for internal and external customers

Skills & Experience Required

• Extensive hands-on experience with PySpark, including performance optimisation
• Deep working knowledge of Databricks (development, architecture, and operations)
• Proven experience working with Airflow for orchestration
• Proven track record in managing and securing PII data, with GDPR compliance in mind
• Experience in data governance processes;
  Alation experience preferred, but similar tools welcome
• Strong SQL skills and experience optimising complex queries
• Strong experience in handling and transforming semi-structured data
• High competency in programming, with a focus on clean, efficient, and production-quality code
• Demonstrated ability to…