Data Scientist working at HP analyzing complex data sets using statistical techniques. Developing data - driven models and insights to improve organizational performance while mentoring project teams.
About the role
- Engineering Manager for Teya, leading analytics engineering team to rebuild enterprise data warehouse and drive business analytics.
Responsibilities
- Lead, coach, and grow a high-performing analytics engineering team
- Own the technical direction around data warehouse design, modelling, and modernisation
- Ensure best practices in dimensional modelling, data quality, testing, and documentation
- Collaborate with embedded analytics teams to build and maintain trusted, scalable data products
- Plan, prioritise, and deliver projects in alignment with business goals and timelines
- Review and contribute to technical designs, DBT models, SQL logic, and pipeline architectures
- Introduce and enable AI-driven analytics and automation across data products where appropriate
- Drive Snowflake cost optimisation and ensure efficient resource usage across environments
- Improve automation, data lineage, observability, and self-service capabilities
- Work closely with Data Engineering and Platform teams on roadmap alignment and resource planning
- Foster a culture of continuous improvement, knowledge sharing, and operational excellence
Requirements
- Strong technical background with hands-on experience in data warehouse design and development
- 5+ years in data engineering, analytics engineering, or equivalent
- 2+ years leading or managing technical teams
- Deep understanding of dimensional modelling and data warehousing principles (star/snowflake schemas, slowly changing dimensions, etc.)
- Expert SQL and strong experience with DBT and modern ELT pipelines
- Experience with Snowflake and AWS services
- Experience managing and delivering complex data or analytics projects
- Ability to guide architectural decisions and uphold engineering standards
- Strong communication skills and stakeholder management experience.
- Nice to Have: Python experience for pipeline development or automation; Exposure to AI/ML–assisted analytics or productivity tooling
Benefits
- Flexible working hours
- Health Insurance
- Meal Allowance
- 25 days of Annual leave (+ Bank holidays)
- Public Transportation Card
- Frequent team events & activities in the office and outside
- Office snacks every day
- Friendly, comfortable and informal office environment.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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