Pleo - Analytics Engineer (mid-level)
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Requirements
• Solid experience working with dbt and modern cloud data warehouses like BigQuery. • Strong SQL skills and experience building well-structured, reusable models in a layered architecture. • Ability to translate messy or ambiguous business logic into clean, performant data transformations. • Familiarity with Git-based workflows, version control, and basic CI/CD practices for analytics code. • A strong sense of ownership and responsibility for your work, pragmatic problem-solving and stakeholder management skills. • A SQL coding exercise you complete via our secure coding platform • A Hiring Manager interview: A 60-minutes meeting with the team manager to deep dive into your technical experience, domain knowledge and project experience. • A Team interview: a 60-minutes interview with the team where we’ll deep dive into your analytical approach and business domain knowledge. • Last time we hired an Analytics Engineer, we received a total of 268 applications but only 8 were selected for an intro call. Some of the key reasons why previous candidates didn’t make it past the application screening stage include: • Every single application we receive is reviewed by a human (yes, hundreds of them) because we believe that candidates' efforts should be matched by an equal level of human care. This means that we expect a similar level of attention put into your application. Read and answer the application questions carefully, they make a huge difference in our decision-making process.
Responsibilities
• Build and maintain business-critical data models in dbt that power credit, payments, and fraud/AML reporting and decision-making. • Partner closely with stakeholders, Data Engineers and Data Analysts to align on requirements, ownership, and success criteria. • Contribute to our semantic layer (LookML) to enable consistent and scalable reporting as well as self-serve exploration. • Own and improve data quality through testing, documentation, monitoring, and proactive issue detection (including working with orchestration where needed, e.g. Airflow/Astronomer). • Contribute to shared analytics engineering ways of working: code reviews, standards, reusable patterns, and reducing technical debt. • In your first few months at Pleo, you will: • Dive deeper into at least one of our business-critical domains (Credit, Payments, Fraud/AML) and learn the reliability expectations around those pipelines and models. • Grow your career in a supportive culture where you'll gain cross-functional insights from our team including Data Engineers, Data Analysts, and Analytics Engineers, as well as from business stakeholders. • Expand your impact by enabling analysts and stakeholders to work more effectively with trusted, well-documented data. • We’re committed to helping you develop your career, whether that means taking on bigger projects, stepping into leadership, or acquiring new skills in data and analytics. • The location • The role can be based in Denmark, Portugal, Spain or the UK. We can hire either remotely, hybrid or in office but you need to be physically based in any of those countries. • Please note we are unable to offer visa sponsorship for this role in any of the listed locations you find in the job info so you will need to have a valid right to work. • We’re happy to share more about our approach to pay and this range during your first call with us!
Benefits
• This role is for you if: • You are comfortable working following high engineering and data platform standards (e.g. CI/CD, code reviews, PRs, established data governance…). • You are excited to partner closely with non-technical business domain experts and to learn from senior colleagues from many data disciplines. • You want to deepen your knowledge and expertise in the areas of payments, credit, and fraud/AML. • This role may not be for you if: • You want to go deep in one domain for a long time. As an AE in the CDP team, you will be supporting multiple domains and shared definitions, which can mean a lot of context switching. • You prefer lower-stakes analytics work. The CDP team works on business critical (credit, payments, fraud/AML) matters, so reliability and operational discipline are a bigger part of the job. • You find it difficult to proactively engage with colleagues outside of the Data world. • Your own Pleo card (no more out-of-pocket spending!) • Lunch is on us for your work days - enjoy catered meals or receive a lunch allowance based on your local office • Comprehensive private healthcare - depending on your location, coverage options include Vitality, Alan or Médis • We offer a minimum of 28 days of holiday + your public holidays • For our Team, we offer both hybrid and fully remote working options • Option to purchase 5 additional days of holiday through a salary sacrifice • We use MyndUp to give our employees access to free mental health and well-being support with great success so far • The Interview Process • Intro call: A 30-minutes chat with our Talent Partner to discuss the role and your background. • A SQL coding exercise you complete via our secure coding platform • A Hiring Manager interview: A 60-minutes meeting with the team manager to deep dive into your technical experience, domain knowledge and project experience. • A Team interview: a 60-minutes interview with the team where we’ll deep dive into your analytical approach and business domain knowledge. • Transparency is important to us so we also wanted to share some insights about what we’re looking for in applications to ensure you can set yourself up for success! • Last time we hired an Analytics Engineer, we received a total of 268 applications but only 8 were selected for an intro call. Some of the key reasons why previous candidates didn’t make it past the application screening stage include: • We receive a lot of CVs, and many of them are AI-generated. We love seeing people leverage AI—it’s a big focus for us internally too—but without human intervention, these CVs can sometimes become generic and fail to show a candidate in the best light. What we're really looking for is the specific details of real impact that only you—not AI—know from your previous experience. A top tip from us is to use the “Achieved X, as measured by Y, by doing Z” formula (credit: Laszlo Bock, ~2014) to give a really clear picture of what you’ve worked on. A final note: including links to your previous companies' websites is a huge help and allows us to truly understand your background. • Every single application we receive is reviewed by a human (yes, hundreds of them) because we believe that candidates' efforts should be matched by an equal level of human care. This means that we expect a similar level of attention put into your application. Read and answer the application questions carefully, they make a huge difference in our decision-making process. • Profile to role fit: there was misunderstanding about the type of experience we expect from an Analytics Engineer and we received many applications from candidates who had never been exposed to a product-led environment or had been exclusively focused on SQL/dbt work when we’re looking for both technical and stakeholders management, as well as team collaboration experience. We’ve taken great care in writing this role description to reflect the reality of the job as best as possible, please ensure you read it carefully and highlight on your CV the experience relevant to what we are looking for.
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