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About the Role
As our Data Lead, you will own all data at TRIP, focusing on collection, modeling, access, and trustworthiness. You will adopt an AI-first approach, leveraging AI for faster development and ensuring data reliability for AI tools. This role involves hands-on architecture and pipeline work, alongside building and managing a team, reporting to the Head of AI Transformation.
Responsibilities
- Own TRIP's data, ensuring quality, definitions, and availability across the UK and US.
- Establish and maintain consistent definitions for core metrics like revenue, margin, and customer retention.
- Manage data governance, access controls, and the secure connection of AI tools.
- Maintain high standards for data cleanliness and accuracy, testing data at all layers and reconciling with source systems and Finance.
- Serve as the primary point of contact for data-related inquiries and develop self-serve solutions for recurring questions.
- Lead the development of the Snowflake data warehouse, including raw data, cleaned layers, and user-facing tables.
- Oversee the dbt transformation layer, covering model design, testing, documentation, and deployment.
- Utilize AI coding assistants for pipeline and model development, testing, and documentation, automating repetitive tasks.
- Manage existing data pipelines, including the BigQuery data lake and feeds from various systems, planning migration to Snowflake.
- Monitor pipeline health, costs, and data freshness, addressing any issues promptly.
- Consolidate and manage UK and US retail data, including EPOS, syndicated market data, and account data.
- Replace manual data exports with automated loads where possible, maintaining records of data sources and refresh dates.
- Integrate retail sell-out data with DTC and marketplace data to provide a holistic view of TRIP's performance.
- Provide reliable reporting on sales, distribution, promotions, and market share to Commercial and Category teams.
- Collaborate with the Digital team to measure marketing's impact on retail sales.
- Hire, manage, and develop a data team, including offshore engineers, and establish team workflows and review processes.
- Develop and execute a roadmap for the data team, prioritizing work based on business impact.
- Manage relationships with data partners and vendors, ensuring deliverables are met.
- Champion data-driven decision-making across the organization, assisting teams in setting measurable goals and conducting proper testing.
- Ensure leadership, Finance, and channel team reporting is sourced from the data warehouse, not spreadsheets.
- Collaborate with the Head of AI Transformation to ensure data is structured for reliable querying by both humans and AI.
- Communicate data insights clearly to non-technical colleagues and train teams on self-service data analysis.
Requirements
- Experience building a modern data stack in a growing business with limited resources.
- Proficiency in writing dbt models and communicating data insights to leadership.
- Minimum of five years of experience in data engineering or analytics engineering, with experience leading a small team.
- Hands-on production experience with Snowflake.
- Strong dbt experience, including modeling, testing, documentation, and deployment.
- Experience designing, building, and maintaining data pipelines from SaaS and ad platforms using tools like Fivetran, Airbyte, or custom connectors.
- Strong SQL skills and Python proficiency for pipelines and automation.
- Experience with retail data, including EPOS, retailer portal data, and syndicated market data (e.g., Circana, NielsenIQ, SPINS).
- Proven track record of building and managing a data team, including hiring and developing talent.
- Experience setting data governance, metric definitions, and access controls.
- A rigorous, detail-minded approach to data analysis and validation.
- An AI-first working methodology, utilizing tools like Claude, Cursor, or Copilot.
- Clear communication skills and confidence in aligning teams with differing data perspectives.
- Experience managing offshore or remote engineers is a plus.
- Experience in e-commerce, DTC, food, drink, or FMCG, including Shopify or Amazon data is a bonus.
- Experience with BigQuery or Google Cloud, or migrating between data warehouses is a bonus.
- Experience feeding planning, forecasting, or finance tools from a data warehouse is a bonus.
- Experience connecting AI tools or LLMs to company data is a bonus.
- Experience with BI or visualization platforms like Power BI or Looker is a bonus.
Skills
- Snowflake
- dbt
- SQL
- Python
- Data Modeling
- Data Pipelines
- Data Governance
- Retail Data Analysis
- EPOS Data
- Syndicated Market Data
- AI Tools
- Team Leadership
- Communication
Location
- Notting Hill, London
Work Type
- Hybrid (Four days in office, one from home)
Experience Level
- 5+ years in data engineering or analytics engineering
- Experience leading a small team
Benefits
- Annual bonus
- Equity
- 24 days' holiday
- Birthday off
- TRIP product discount
- Friends & Family codes
- Mental wellbeing support (Self Space therapy, Calm app)
- Private healthcare (Vitality)
- 50% off Virgin Active gym membership
- Breakfast and snacks provided
- Monthly Dream Drops CBD Oil allowance
- Up to two weeks working abroad annually
- Dog-friendly office
- Regular team socials and events
About the Company
- TRIP's mission is to create calm in the everyday chaos by offering next-generation wellness products focused on mental wellbeing.
- Founded in 2019, TRIP is the world's #1 Calming Beverage Brand, offering award-winning drinks and wellness products crafted with botanicals and adaptogens.
- The company has rapidly expanded globally, generating over $100 million in sales and is available in major retailers and online.
- TRIP aims to become the global leader in calming drinks, synonymous with calm like Red Bull is with energy.
- The company culture is fast-paced, ambitious, and committed to prioritizing mental wellbeing.