JustJoin.IT Hybrydowo Senior

Business Data Analyst

Straal

⚲ Warszawa

Do uzgodnienia

Wymagania

  • SQL
  • Database structure
  • AB testing
  • Data analysis
  • Python
  • AI

Opis stanowiska

We're currently looking for a Business Data Analyst to the DataHub to help us optimize conversion rates, detect anomalies, and design seamless data pipelines for our payment systems. This role is not just about analytics - it’s about deeply understanding the business, playing Sherlock Holmes with data, and turning insights and observations into real product improvements. It’s a path to becoming a true domain expert. 
If you have experience in SQL, Python, BI tools, and a strong analytical mindset, this could be a great opportunity to take the next step in your career. We’d love to have you in our Warsaw office, where our team thrives on in-person collaboration, with the flexibility to work remotely when needed.

Straal is an international provider of payment, optimisation, and fraud prevention solutions for future-minded small and medium businesses. The company offers a comprehensive suite of products that make accepting digital payments easy, convenient, and fully secure for merchants and their customers. From subscription engines, through card payments and open banking solutions to alternative payment methods, Straal offers everything that fast-developing companies need for every customer journey.
Your responsibilities:


Insights Generation: Analyze data to optimize conversion funnels, track anomalies on micro and macro scale, and recommend actions to enhance performance.



AB Testing and Benchmarking: Conduct experiments and performance benchmarking to drive evidence-based changes.

• Analytical Tool Development: Create and improve tools to make data easily accessible for stakeholders.
• Financial Analysis: Dive into transactional data for financial insights.
• Pipeline Design: Build and maintain robust data pipelines to gather and process transaction data from payment systems. (Nice to have)
Minimum qualifications:
• Proactive ownership: Someone who wants to understand the full context of our business, proactively identifies opportunities for gains and optimizations, and doesn't wait to be told what to analyze next.

• Data-driven decision-making: Someone who connects the dots between data and real business impact, with the ability to make decisions without getting stuck in analysis paralysis.
• Result-orientated mindset with focus on continuous improvement: Someone who naturally challenges the status quo, constantly seeking ways for improvements and delivering measurable results.
• Experience: Proven experience in data analysis, ideally in payments, banking, or related industries.
• Technical skills:
• Experience with SQL (e.g., PostgreSQL)
• Knowledge of database structures and optimization.
• Proficiency in data analysis and visualization tools like Metabase, Looker, PowerBI or similar.
• Experience in building analytical toolsets.
• Basic Python scripting skills.
• Ability to use AI tools effectively and responsibly to accelerate analytical work (SQL, Python, data exploration, documentation, and automation).
• Ability to handle non-standard data files beyond standard GUIs, to normalize inputs.

• Professional proficiency in English.

Nice to have:
• Ability to design and manage data pipelines for smooth data flow (nice to have).

🔍 Dekoder Ogłoszenia

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playing Sherlock Holmes with data
Oczekuje się od Ciebie samodzielnego i dogłębnego poszukiwania przyczyn problemów w danych, często bez jasno określonych wytycznych.
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turning insights and observations into real product improvements
Twoje analizy muszą prowadzić do konkretnych zmian w produktach, co może wymagać silnych umiejętności komunikacyjnych i wpływania na innych.
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It’s a path to becoming a true domain expert
Może to oznaczać, że będziesz mocno skupiony na jednej, specyficznej dziedzinie, a rozwój w innych obszarach może być ograniczony.
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thrives on in-person collaboration, with the flexibility to work remotely when needed
Chociaż praca zdalna jest możliwa, nacisk kładziony jest na współpracę stacjonarną, co może oznaczać częste wizyty w biurze.
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track anomalies on micro and macro scale
Oczekuje się od Ciebie wykrywania zarówno drobnych, jak i znaczących odchyleń w danych, co może być czasochłonne i wymagać precyzji.