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Open nowPosted 3 days ago

Sr. Manager, Analytics Engineering & Data Science, EMEA

job-room.ch86,007 open roles

Where
Zug, ZG, Switzerland
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Your applicationOpen nowSr. Manager, Analytics Engineering & Data Science, EMEAjob-room.ch · Zug, ZG, Switzerland

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This job: posted 3 days ago

The posting

Ready to make your next big professional move? Join us on our journey to achieve our big dream of building the most loved restaurant brands in the world.

Restaurant Brands International Inc. is one of the world's largest quick service restaurant companies with nearly $45 billion in annual system-wide sales and over 32,000 restaurants in more than 120 countries and territories.

RBI owns four of the world's most prominent and iconic quick service restaurant brands – TIM HORTONS®, BURGER KING®, POPEYES®, and FIREHOUSE SUBS®. These independently operated brands have been serving their respective guests, franchisees and communities for decades. Through its Restaurant Brands for Good framework, RBI is improving sustainable outcomes related to its food, the planet, and people and communities.

RBI is committed to growing the TIM HORTONS®, BURGER KING®, POPEYES® and FIREHOUSE SUBS® brands by leveraging their respective core values, employee and franchisee relationships, and long track records of community support. Each brand benefits from the global scale and shared best practices that come from ownership by Restaurant Brands International Inc.

Our opportunity:

Restaurant Brands International (RBI) is looking for a Senior Manager, Analytics Engineering & Data Science to lead a critical team supporting our EMEA business. This is a highly visible role sitting at the intersection of data engineering, data science, AI Implementation, and analytics — responsible for driving the technical direction and operating model for how data is engineered, modeled, governed, and turned into decisions across our EMEA markets.

The role requires people leadership to build and scale a team, deep technical credibility across the modern data stack (Inclusive of building scaled LLM-enabled products), and the judgment to prioritize across competing demands from Analytics, Marketing, Digital, Operations, Finance, and Franchise stakeholders across all EMEA markets. The ideal candidate will be equally effective in architecting a 3-year data strategy, coaching a data scientist through a forecasting model, presenting a data strategy to senior leadership, or designing an AI-enabled pricing intelligence platform (Front and Back end).

This role reports into the Senior Director, Analytics, Insights, Data, and Digital, EMEA

RBI follows a 5 day, in-office work schedule to support collaboration. Candidates should be comfortable working onsite 5 days per week.

Your Roles & Responsibilities:

Team Leadership & Strategy

Build, lead, and mentor a growing, multi-disciplinary team spanning analytics engineering, product development, data science, data engineering, and data operations across EMEA. Collaborate effectively with several global data and technology teams in a matrix-style organization. Set team strategy, priorities, and ways of working with a particular focus in growing the data talent bench across the EMEA region. Data Strategy & Architecture

Own the short- and long-term data strategy for EMEA including the target data architecture and platform roadmap, build-vs-buy vendor/tooling decisions, and how the region's data investments are prioritized and sequenced against business demand. Collaborate with global data teams to optimize the design, scalability, and reliability of EMEA's data pipelines, warehousing, and architecture (primarily Snowflake and AWS). Ensure alignment with global data standards while adapting to local market needs, particularly EU GDPR regulations. Data Product & Design

Own and build all key EMEA data products, interfacing with international teams for full global productionization (e.g., semantic data layer to enable AI chatbots). Lead key Analytics & Data Science product design and delivery in collaboration with internal teams and external consulting partners (e.g., Pricing Intelligence Platform & Software Suite). AI & Emerging Capability

Identify opportunities to apply AI/LLM capabilities within analytics and data science workflows to improve productivity and unlock new insight. Prototype and pilot emerging AI/ML capabilities (e.g., GenAI-powered insight generation, forecasting copilots, automated anomaly detection) in partnership with global AI enablement teams. Evaluate emerging tools, platforms, and vendors, and make build-vs-buy recommendations for AI-driven data capabilities. Data Operations & Governance

Oversee data quality, cataloging, and documentation of process flows across the EMEA data estate. Establish scalable prioritization (e.g., ticketing) and governance practices as the team and data estate grow. Define and maintain data governance standards — ownership, access, lineage, and retention — in coordination with legal, security, and global data governance teams. Ensure compliance with GDPR and other regional data privacy and regulatory requirements across all EMEA data assets and pipelines.

Your skills and experience:

Bachelor's degree or higher in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field. 6-10 years of experience across data engineering, analytics, or data science, within QSR, restaurant or hospitality industry. 3+ years of direct people leadership managing technical teamswith proven ability to build, lead, and grow multi-disciplinary technical teams, including hiring, mentoring, and performance management.. Substantial experience leading cross-functional product teams with a clear track record deploying tangible – value-add Analytics & data products. Deep, hands-on expertise in SQL, and cloud data warehousing; Snowflake and AWS experience are also required. Experience with AI/LLM enablement or GenAI tooling application in data & analytics workstreams. Strong data visualization skills (Tableau, Power BI, or similar) and the ability to translate complex analysis into clear recommendations. Experience with workflow orchestration (e.g., Airflow, Dagster), and modern data stack tooling (e.g., dbt, Terraform). Programming skills in Python and/or R, with experience applying statistical or machine learning techniques (forecasting, clustering, experimentation, etc.) a plus. Excellent communication and executive presentation skills; comfortable engaging a range of stakeholders across multiple markets and functions. Experience operating across multiple countries or markets, with awareness of data privacy regulation (GDPR) and cross-border data considerations. Relevant certifications (e.g., Snowflake SnowPro, AWS Certifications) are a plus. Fluency in English is required.

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