About the job
About Us
SharkNinja is a leading global product design and technology organization, renowned for its diverse portfolio of highly-rated lifestyle solutions that enhance the lives of individuals in homes worldwide. With two trusted global brands, Shark and Ninja, we have a remarkable history of delivering groundbreaking innovations to the market. Our commitment to consumer needs has enabled us to expand across various product categories, significantly boosting our growth and market share. Headquartered in Needham, Massachusetts, we employ over 4,100 associates, and our products are available through major retailers, both online and offline, as well as through distributors globally.
About the Role
As we enhance our data and AI capabilities, we are on the lookout for a Data Automation & AI Analyst to become a vital part of our Global Automation and Visualization team. This position, based in the UK, plays a crucial role in our mission to integrate intelligent automation and AI-driven reporting throughout the organization.
Reporting to the Analytics Director, the Data Automation & AI Analyst will focus on constructing and sustaining scalable data pipelines, automating reporting processes, and crafting AI-assisted solutions that provide quick and reliable insights across essential commercial functions.
This role is perfect for a technically adept, innovative individual who is enthusiastic about automation, AI tools, and data engineering — and who desires to be at the forefront of utilizing technology to facilitate smarter, faster decision-making.
What You'll Do
Data Engineering & Pipeline Development
- Design, build, and maintain SQL-based data pipelines within Snowflake to consolidate and transform data from various sources including POS, retail, and internal systems.
- Guarantee data accuracy, consistency, and integrity across reporting datasets.
- Employ Python for automating regular data processes, minimizing manual effort while enhancing the reliability and speed of data delivery.
- Identify and rectify data quality issues, collaborating with upstream data proprietors to implement enduring solutions.
- Explore and apply AI-assisted methodologies for data transformation, anomaly detection, and more.

