Senior Data Analyst at Delivery Hero

Capital City of Prague, Prague, Czechia -

Full Time

Start Date

Immediate

Expiry Date

10 Jun, 26

Salary

0.0

Posted On

12 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Data Modeling, Reporting, Data Visualization, Looker, Tableau, BigQuery, dbt, Financial Analysis, Stakeholder Collaboration, Business Acumen, Mentorship, Data Quality, Benchmarking, Process Standardization, Critical Thinking

Industry

technology;Information and Internet

Description

Company Description foodora 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 70 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. Job Description As a Senior Data Analyst you will leverage your expertise to directly impact the financial performance and reporting for our 16 markets by delivering scalable data and reporting assets, actionable insights, and advanced analytics solutions. In this role, you will work closely with finance teams at various levels of the organization to understand requirements, standardize processes, and develop reporting. You will also own benchmarking business performance leveraging and optimizing our portfolio of category position solutions. This high-impact role requires a self-starter who is capable of effectively balancing trade-offs between speedy delivery of regulatory requests and long-term investments in strategic data assets in order to enhance growth, efficiency, and competitive advantage across multiple markets. Responsibilities: Strategic Reporting & Visualization: Design and build compelling, user-friendly dashboards (e.g., Looker, Tableau) that enable key financial reporting and facilitate decision-making for business stakeholders. Define KPI frameworks, support standardization of financial processes, and ensure metrics align with business objectives. Advanced Data Modeling & Analysis: Lead the development of complex SQL models to transform large datasets into scalable reports and actionable insights, using tools like BigQuery and dbt. Leveraging critical thinking in questioning existing solutions, and high ownership in developing new ones. Championing high standards in communication and deliverables. Functional Knowledge and Business Acumen: Quickly developing an excellent understanding of the business and its key financial processes and category position asset portfolio. Leveraging AI to document and disseminate knowledge. Building on existing assets to create future success-enablers. Stakeholder Collaboration & Data Advocacy: Partnering with senior finance and business leaders to co-define key metrics, identifying process optimization opportunities, and translating analytical findings into actionable insights. Being a strong advocate for building strategic analytical partnerships, as opposed to just providing data. Prioritization: Aligning analytics efforts with the highest business priorities. Directly engaging finance and business partners in understanding value vs. effort trade-offs. Ensuring that the team is focused on delivering the highest-value work at any given time. Transparency & Backlog Management: Maintaining clear visibility into the team’s project backlog, providing regular updates and insights to stakeholders. Actively seeking and incorporating feedback to continuously improve analytics processes and outputs. Mentorship & Development: Provide guidance and mentorship to junior analysts, enhancing their technical skills and fostering a collaborative team environment. Data & Reporting Consistency: Balancing speed and adherence to SLAs with a commitment to data consistency, avoiding redundant work and ensuring alignment with the organization’s ethos of a single source of truth and standardized processes for financial and other reporting. Rigorous Standards in Data Quality: Establishing, providing ongoing evaluations, and making strategic recommendations on future enhancements in data accuracy, validity, and velocity, both of analytics outputs created internally, and of our portfolio of category position solutions provided by external partners. Find out more about our Data Analytics folks here: Turn insights into impact! Looking for a career in data analytics? This could be the opportunity for you! Qualifications Bachelor’s degree in Finance, Statistics, Mathematics, Economics, Computer Science, or a related field. 5+ years of experience in financial or data analytics with a strong focus on SQL, data modeling, reporting, and data visualization. 3+ years of experience with Financial datasets and a solid understanding of the business processes driving controlling, risk, payments, and other key finance functions. Proven track record of developing data assets, reporting solutions, and strategic insights to drive growth, efficiency and/or cost savings. Proficiency with advanced SQL (preferably with BigQuery or similar DWH) and experience in Looker or Tableau. Familiarity with dbt and SAP is a plus. Strong analytical and problem-solving skills, with experience in translating data and financial requirements into effective solutions Demonstrated success in building and scaling analytics solutions in dynamic, fast-paced environments. Strong business acumen with excellent communication and presentation skills. Ability to work independently on complex projects and deliver high-impact results in a fast-paced environment. Experience with market analysis and competitive intelligence (ex. Nielsen, AlphaSense, or similar) would be a plus. To help us review applications consistently, please attach a copy of your resume in English. We appreciate your effort and look forward to learning more about you! Additional Information -

Responsibilities

The Senior Data Analyst will design and build compelling dashboards for financial reporting, define KPI frameworks, and lead the development of complex SQL models to transform large datasets into scalable reports and actionable insights. Responsibilities also include partnering with senior leaders to translate analytical findings into actionable insights and providing mentorship to junior analysts.