About the company:

Home Bargains is the 20th largest privately owned company in the UK, with 550 stores and a £3 billion annual turnover. As we move into the era of Big Data, Home Bargains is producing and consuming data at a rapidly increasing rate. We recognise that becoming more data-driven and embracing new technologies (e.g. Machine Learning and AI) will play a crucial role in increasing sales, reducing costs, boosting efficiency and allowing Home Bargains to remain competitive in the retail sector for years to come. We’ve already made great progress towards this goal in the last year, and now we are on the lookout for the top data and engineering talent to grow our team and build on this success.

About the Job:

You will be the first full-time Data Engineer to join our new Data Analytics and AI team, which sits within the wider Innovation function, you will have the opportunity to have considerable influence over the direction of data engineering workstreams and strategy, with ample room for innovation. Working alongside our Data Scientists and Analysts, you will be responsible for our data warehouse infrastructure, ensuirng that data flows consistently from our business operations to the teams that need it most.

Day to day, you will work with colleagues to design and implement the infrastructure needed to collect, transform, clean and organise data from across the organisation. You will create the data products that sit at the heart of our data led strategy, delivering insight and underpinning our ML & AI ambition.

Core Responsibilities:

Build and maintain data feeds

  • As a Data Engineer, your primary responsibility is to build and maintain the data feeds that underpin the work of the Data Analytics and AI Team
  • You will be responsible for the entire end-to-end of data provisioning, from identification and scoping through design, implementation, testing and ongoing management
  • You will need to employ engineering best practices to create data feeds that are robust, scalable and efficient

Data Warehouse management

  • The core of our data platform is a modern, scalable cloud data warehouse, from which we develop and deploy data products for use across the business
  • You will play a leading role, alongside your IT colleagues, in the management and further development of this critical infrastructure
  • In addition to the warehouse itself, you will use Kubernetes to deploy containerised data transformation applications and manage orchestration with Apache Airflow

Data stewardship

  • The quality of our data assets is essential to their adoption and value generation. You will play a key role in ensuring data quality through the development of automated data validation and cleansing processes. Maintaining effective documentation is essential for usability of data assets. Your role will include documentation of data schemas, data lineage and transformation, including contributing to the data risk and control registers

Maintenance of deployed applications and reports

  • Ensuring that necessary data is continually fed to deployed data science applications and analytics reports
  • Monitoring data flows, job orchestration and patches/releases as necessary

New applications and reports

  • Assisting Data Scientists and Data Analysts in provisioning data for applications and reports in development
  • Optimising data processing and, where appropriate, applying distributed methods

We are looking for someone who has:

  • A good understanding of retail-orientated business processes and systems
  • Strong knowledge of data warehousing solutions, ETL/ELT processes and data quality issues
  • Excellent SQL skills, demonstrated across a range of professional projects
  • Proficiency in Python or another data-oriented programming language
  • Experience in core software engineering practices, e.g. development lifecycle, Git version control, continuous integration
  • Experience with Cloud computing, distributed frameworks and containers

We would love to hear from you if you have any of the following:

  • Experience working with Big Data technologies (i.e. Spark, Kafka, EMR, etc.)
  • Experience deploying analytics workloads to Kubernetes (or similar)
  • Some knowledge of machine learning
  • Previous experience working as part of a data team
  • Experience using workflow orchestration engines (preferably Apache Airflow)

What you will get in return:

  • 28 days of paid annual leave (inclusive of public holidays), increasing to 33 days after 5 years of service
  • Flexible working
  • Company pension Scheme
  • 10% Staff Discount at Home Bargains flagship store
  • The opportunity to work with genuinely cutting-edge technology in the field of data engineering within a company that has a genuine drive to be driven by data.