About Charlotte Tilbury Beauty
Founded by British makeup artist and beauty entrepreneur Charlotte Tilbury MBE in 2013, Charlotte Tilbury Beauty has revolutionised the face of the global beauty industry by de-coding makeup applications for everyone, everywhere, with an easy-to-use, easy-to-choose, easy-to-gift range. Today, Charlotte Tilbury Beauty continues to break records across countries, channels, and categories and to scale at pace.
Over the last 10 years, Charlotte Tilbury Beauty has experienced exceptional growth and is one of the most talked about brands in the beauty industry and beyond. It has become a global sensation across 50 markets (and growing), with over 2,300 employees globally who are part of the Dream Team making the magic happen.
Today, Charlotte Tilbury Beauty is a truly global business, delivering market-leading growth, innovative retail and product launches fuelled by industry-leading tech — all with an internal culture of embracing challenges, disruptive thinking, winning together, and sharing the magic. The energy behind the brand is infectious, and as we grow, we are always looking for extraordinary talent who want to be part of this our success and help drive our limitless ambitions.
About The Role
As data is the core to how we serve and attract our growing customer base, our data team is expanding to keep up with demand. The need for a new function, that is responsible for streamlining how data products are developed and ultimately increasing the speed at which insights are gleaned from data, has become too important to ignore. As a Senior DataOps Engineer you will one of the first to apply agile development, DevOps and lean manufacturing principles to data analytics not just at Charlotte Tilbury but across the industry. You will work alongside the Lead DataOps Engineer to make this a reality whilst collaborating with the Data Engineering, Analytics, Data Science & Insights Teams as well as working with other functions across the business.
You will already have experience working in agile development teams on ELT pipelines where data is the product and understand the common pitfalls of what often makes development slow or inefficient. You will have the opportunity to make a positive impact on data engineering and analytics teams reducing the time spent on error resolution allowing them to focus on high value activities. You will take ownership of the data factory and build tools and mechanisms to monitor its operation in real-time so that errors are resolved before they can affect downstream data consumers.
As the DataOps Engineer you will
- Identify opportunities to streamline the development of data products by advocating a culture that encourages reuse, automation, and common standards.
- Build solutions that automate repetitive manual steps in the data pipeline development life cycle
- Design and build solutions that can identify and encrypt sensitive data across the data lake
- Review existing data engineering design patterns and seek ways to improve
- Implement solutions that ensure good data governance across the organisation
- Increase the discoverability and transparency of data across the organisation
- Ensure data is secure and compliant to rules and regulations whilst protecting our customers.
- Explore and investigate unchartered technologies that contribute to improving our data warehouse whilst minimising our technical debt.
- Mentor colleagues at all levels on new ways of working and improved development practices.
- Lead by example in the development of new solutions, setting standards for the data team to adhere to and ensure its adoption.
- Look for and act on opportunities for growing both the skills and capacity of the data team.
- Support the optimisation of spend on our tech stack.
- Support in keeping the DataOps strategy relevant and have shared accountability for DataOps continuing to generate value for the data team.
- Support the planning of work and the development of the DataOps roadmap.
Key Selection Criteria
You will be familiar with most of the following technologies
- Cloud ProviderGoogle Cloud Platform
- Source controlGitHub
- Data Engineering tools =Looker, Snowplow/Google Analytics or similar, Cloud Composer/ Airflow, BigQuery, Dataform, Dataflow
- Data Governance tools =Data Catalog, Data Loss Prevention, Dataplex
- Agile development tools =JIRA
- DevOps tools =Terraform, Docker, CircleCI
- Languages =Python, Bash, SQL, JavaScript
You will possess good knowledge of
- CI/CD pipeline development and maintenance
- Git workflows and branching strategies
- Test driven development (TDD)
- Data pipeline/warehouse monitoring
- Agile methodology/approach
- Common pain points experienced by data engineering teams
- Understanding of common data engineering patterns
- DataOps purpose and what it strives to solve
At Charlotte Tilbury Beauty, our mission is to empower everybody in the world to be the most beautiful version of themselves. We celebrate and support this by encouraging and hiring people with diverse backgrounds, cultures, voices, beliefs, and perspectives into our growing global workforce. By doing so, we better serve our communities, customers, employees - and the candidates that take part in our recruitment process.
If you want to learn more about life at Charlotte Tilbury Beauty please follow ourLinkedIn page!
