Data & Analytics at Dyson
Data and analytics excellence at Dyson is delivered by a diverse and collaborative global community, at the heart of that community is a hub team that enables all others: In Dyson’s Data Analytics team, there has been significant investment into cloud technologies and tools; combined with an expansive scope and no shortage of ambition and momentum, Dyson Data Analytics team is recognised throughout the organisation to the highest level as critical to all of Dyson's strategic objectives.
With a ‘one-team’ approach, the global community is on a mission to:
- Evolve existing solutions to stay ahead
- Embed emerging solutions to capitalise on potential benefits
- Deliver conceptualised & future solutions to introduce net-new capability
The Team
As the ‘hub’ team delivering the data, technology and community provision enabling Dyson’s global data and analytics capabilities, Dyson Data Analytics team have end-to-end responsibility for data from foundations (DQ, MDM) to management (data platforms, integrations), to value realisation (analytics enablement and delivery).
Dyson Data and Analytics team is a multi-disciplinary, global team providing round-the-clock development and operations - including product and project management, community enablement, governance, data architecture, data engineering, data science, and analytics expertise.
Involved with every aspect of Dyson’s global business - from finance to product development, manufacturing to owner experience – the team is seeking to deliver solutions generating impressive and tangible business value.
The Role
At Dyson, Data Engineers are Software Engineers specialising in building data intensive applications.
You will be responsible for:
- Delivering Data Engineering excellence in the end-to-end delivery of complex data engineering projects and programs for Dyson
- Reviewing technical designs and providing feedback
- Designing and building end-to-end data solutions for analytics
- Migrating existing pipelines onto the platform
- Involve in deployment, testing activities with hands on engineering and automation experience including CI/CD/CD and DataOps mindset
- Adapting quickly to change in requirements and be willing to work with different technologies if required
- Develop and maintain data pipelines in a Backend/Distributed Data Systems team while remaining hands-on is very important
- Strengthening data quality and reliability
- Improving data lineage and governance
- Progressing standards and best practices for the platform and operational excellence
- Maintaining our documentation culture
The ideal candidate will
- Have 3 - 4 years of relevant experience
- Write clean code that can be easily understood by others
- Be able to understand and improve legacy code
- Identify and build abstractions and tools to solve recurring challenge
- Apply best practices and ways of working among our global data engineering team
- Provide constructive feedback through PRs and pairing
- Seek to close gaps in documentation
Our Tech Stack
Our modern data stack constantly evolves over time as it strives for best-in-class technical capabilities, scalability and efficiency. We don’t require applicants to have experience with all these technologies, but are always keen to learn and maximise best use of each and as a whole
- Git for source control management
- Terragrunt for infrastructure as code
- GCP for infrastructure
- BigQuery for data warehousing
- Apache Beam and Python for ELT (Extract Load Transform)
- Airflow for orchestration
- dbt (SQL) for data modelling
- Datadog for monitoring
- Fivetran
You Should Apply If
- You feel strongly about data and want to empower the organisation with it
- You seek technical excellence and is self-driven and motivated
- You want to build robust, scalable and reliable software and solutions
- You have experience with SQL and strong programming skills in a modern language (Python/Kotlin/Java/Scala)
- You are comfortable writing production grade software that solves problems often presented with ambiguity
- You proactively identify challenges and opportunities, and seek to improve the team as a whole