Data Observability Specialist

About Us :

With over 200 brands sold in more than 180 countries, we’re the world’s leading premium drinks company. Every day, over 27,000 dedicated people come together at Diageo to build the magic behind our much-loved brands.

Our founders, such as Arthur Guinness, John Walker, and Charles Tanqueray, were visionary entrepreneurs whose experienced minds helped craft the alcohol industry. And through our people, their legacy lives on. Join us, and you’ll collaborate with talented people from all corners of the world. Together, you’ll innovate and push boundaries, crafting a more inclusive and balanced future that we can all be proud of.

With diversity at our core, we celebrate our people's individual passions, commitments and specialist skills. In our encouraging culture, your voice will be heard and you’ll be empowered to be you. Just bring your ambition, curiosity and ideas, and we’ll celebrate your work and help you reach your fullest potential

Purpose of Role :

The purpose of this role is to develop, evolve the new Data Quality Framework based on the DQ2.0 roadmap. that will drive delivery and maintenance of high-quality data for the DDH Data Assets, Project teams. In addition, resolve technical issues and offer consulting inputs for driving the data quality, design, development of Data Assets function.

Data Quality (DQ) Observability

• Familiarity with cloud platforms and containerization technologies (Data Bricks).
• Proficiency in scripting and automation using languages such as Python,
• Excellent problem-solving skills with the ability to analyse complex issues and provide efficient solutions.
• Good communication skills and the ability to collaborate effectively across teams.
• Understanding of Agile and DevOps and GIT principles and their application in observability and monitoring contexts.
• Solid experience with instrumentation practices, including metrics, logging, and distributed tracing.
• E2E implementation. Right from requirement gathering and DQ design engaging with the Data Asset owners, development, and reporting.
• Development DQ rules with the help of Databricks
• Presentation of DQ results to the Data Asset Owners and other partners and work with them to build an action plan to improve the DQ results.
• Putting in place specific Data Improvement Plans
• Scale up the DQ framework to all the data assets and more.
• Ensure systems run efficiently, monitoring system performance and handle support in demanding environment.
• Handle the configuration of existing toolset for data quality, KPI system and Reporting.

Proficiency in implementing and maintaining observability tools is a plus

Qualifications and Experience Required

• Degree level education, preferably with overall 6-8 years of experience in SQL, Data warehousing and hands on Data Science
• Must be proficient and have experience in Data Science related technologies.
  • Strong Python/ PySpark and SQL development skills
  • Experience in Azure Databricks
  • Agile development methodology using DevOps and GIT repos.
• Experience with Big Data tools and Cloud environment, especially Azure is a big plus.
• Expertise in converting Functional requirements to technical solutions and present in the business context.
• Experience in working with Hub and Spoke model data lakes, preferably with Diageo context is a big plus.
• Keeping pace with IT trends, innovation, and new developments in technology space
• Good Communication Skills required