Delivery Hero
E-Commerce
SeniorDataAnalyst
Neural analysis suggests this role is
optimal for mid candidates.
“Senior Data Analyst at Delivery Hero. Skills: Data pipelines, Semantic modeling, Audience engineering, Data migration, Data validation. Design, build, and maintain scalable ETL pipelines. Design, build, and maintain dimensional data models”
Industry & Context.
Translate complex business logic; Analyze source data; Define movement logic; Rigorous data validation testing; Remap downstream dependencies; Implement rigorous checks
What They're Looking For.
Must Have
5-8 years of experience in data analytics, Higher education in a quantitative field, Proficiency in writing clean, optimized SQL, Proficiency in writing clean, optimized Python, Hands-on experience with visualization tools
Nice to Have
Experience in advertising industry, Experience designing and analyzing multivariate experiments, Knowledge or experience in digital sales, Knowledge or experience in marketplaces, Experience working with CPG/FMCG companies, Backend Salesforce/SOQL experience
What You'll Do.
and maintain scalable ETL pipelines
and maintain dimensional data models
Translate complex business logic into dashboards
Build and optimize automated audience generation engines
Develop API integrations
Feed user segments into Ad-buying platforms
Develop and manage secure
automated data-sharing pipelines
Share information with external B2B partners
Drive complex data migration projects
Define movement logic
Conduct rigorous data validation testing
Remap all downstream dependencies
Architect and maintain automated data flows
Ensure flawless delivery of data
Implement rigorous checks within data pipelines
Prevent bad data from reaching dashboards
Build tests to verify logical consistency
Maintain unique records
Confirm information meets expected standards
How You'll Work.
Team & Collaboration
Collaborate with Data Engineers; Collaborate with Data Analysts; Translate complex data for stakeholders; Work with business stakeholders; Work with local teams; Work with HQ teams
Communication Scope
Spoken English; Written English
Process & Methodology
Data roadmap execution
Full Job Description
Glovo is part of the Delivery Hero Group, the world’s pioneering local delivery platform, our mission is to deliver an amazing experience—fast, easy, and to your door. We operate in around 65 countries worldwide. Headquartered in Berlin, Germany. Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index. Your work-life opportunity: Within the Brands Ads department in Glovo, we are building the present and future of retail media in +20 markets and we are seeking someone with experience in both advertising and making things happen. We collaborate with +100 brands ads sales colleagues in developing local advertising strategies, and you will play a major role in making their lives easier by providing a strategic vision on the media landscape fueled by data. We are looking for a Sr Data Analyst . for the Brand Ads department who can drive and execute our data roadmap. In this role, you will champion various initiatives that support our primary strategy, working in tandem with business stakeholders from both local and HQ teams. Key Responsibilities: * Data Pipelines & Semantic Modeling: Design, build, and maintain scalable ETL (Extract, Transform, Load) pipelines and dimensional data models. You will translate complex business logic into intuitive, highly performant dashboards (e.g., Looker) for commercial stakeholders. * Off-app Audience Engineering: Build and optimize automated audience generation engines using first-party data. You will develop API integrations that feed complex user segments directly into global Ad-buying platforms (e.g., DV360, The Trade Desk). * Secure B2B Data Integration: Develop and manage secure, automated data-sharing pipelines (SFTP, Cloud Storage Buckets) to seamlessly share information with our external B2B partners. * End-to-End Data Migrations: Drive complex data migration projects by combining advanced Python and SQL. You will own the entire migration lifecycle: analyzing source da
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