Senior Data Analyst (with AI) (#5646)
⚲ Kraków
6 500 - 8 000 USD netto (B2B)
Wymagania
- SQL
- DBT
- AWS
- GCP
- BigQuery
- Data modeling
- AI
- Fintech domain experience
Opis stanowiska
About This Role:
We're looking for a Senior, dbt-specialised Analytics Engineer to build and maintain the business-critical data models behind the client's credit, payments, and fraud/AML reporting. Our client is a fast-growing European fintech company in the business spend management space — corporate cards and related financial products — serving SME and mid-sized business customers across the EU and UK, in a regulated environment with GDPR compliance obligations. Engineering is organized into cross-functional squads, with platform/enabling teams providing shared tooling horizontally. The client already runs an AI-native engineering practice: Claude Code and GitHub Copilot are used daily, supported by a growing library of shared, versioned Skills embedded in key repositories, enabling an end-to-end flow from ticket to implementation, testing and PR in several codebases. AI tool/connector rollout follows an approved-list and pilot process. The client is AWS-first overall; for data platform and analytics workloads it also runs GCP, with BigQuery as the primary data warehouse. Day-to-day coordination is Slack-first, with Linear for ticket tracking, GitHub for code/PR review, and Notion as the knowledge base.
Key Responsibilities:
• Build and maintain business-critical dbt data models.
• Model data powering credit, payments, and fraud/AML reporting (working from aggregated/modeled data, not raw access to real customer/transaction data — see note above).
• Apply strong SQL and data-modelling skills.
• Multiply the output and quality of the squad you join, and share patterns/practice beyond your immediate team so adoption compounds across the organisation.
• Embed directly into a client squad as a hands-on Individual Contributor (not a coaching/managerial role).
Must-Have Skills:
• Experience with dbt.
• Strong SQL and data-modelling skills.
• Experience building and maintaining business-critical data models for credit, payments, and fraud/AML reporting.
• BigQuery — the client's stated primary data warehouse for data platform and analytics workloads.
Nice-to-Have Skills:
• Git — standard, expected tooling, but not explicitly named in the RFP for this role.
We offer:
• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits
We're looking for a Senior, dbt-specialised Analytics Engineer to build and maintain the business-critical data models behind the client's credit, payments, and fraud/AML reporting. Our client is a fast-growing European fintech company in the business spend management space — corporate cards and related financial products — serving SME and mid-sized business customers across the EU and UK, in a regulated environment with GDPR compliance obligations. Engineering is organized into cross-functional squads, with platform/enabling teams providing shared tooling horizontally. The client already runs an AI-native engineering practice: Claude Code and GitHub Copilot are used daily, supported by a growing library of shared, versioned Skills embedded in key repositories, enabling an end-to-end flow from ticket to implementation, testing and PR in several codebases. AI tool/connector rollout follows an approved-list and pilot process. The client is AWS-first overall; for data platform and analytics workloads it also runs GCP, with BigQuery as the primary data warehouse. Day-to-day coordination is Slack-first, with Linear for ticket tracking, GitHub for code/PR review, and Notion as the knowledge base.
Key Responsibilities:
• Build and maintain business-critical dbt data models.
• Model data powering credit, payments, and fraud/AML reporting (working from aggregated/modeled data, not raw access to real customer/transaction data — see note above).
• Apply strong SQL and data-modelling skills.
• Multiply the output and quality of the squad you join, and share patterns/practice beyond your immediate team so adoption compounds across the organisation.
• Embed directly into a client squad as a hands-on Individual Contributor (not a coaching/managerial role).
Must-Have Skills:
• Experience with dbt.
• Strong SQL and data-modelling skills.
• Experience building and maintaining business-critical data models for credit, payments, and fraud/AML reporting.
• BigQuery — the client's stated primary data warehouse for data platform and analytics workloads.
Nice-to-Have Skills:
• Git — standard, expected tooling, but not explicitly named in the RFP for this role.
We offer:
• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits
🔍 Dekoder Ogłoszenia
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dbt-specialised Analytics Engineer
Oczekuje się głębokiej wiedzy i doświadczenia w pracy z narzędziem dbt, co może oznaczać, że nie jest to pozycja dla osób dopiero zaczynających z tym narzędziem.
🔴
working from aggregated/modeled data, not raw access to real customer/transaction data
Nie będziesz miał bezpośredniego dostępu do surowych danych klientów i transakcji, co może ograniczać zakres analiz i wymagać pracy z danymi już przetworzonymi.
🟡
The client already runs an AI-native engineering practice
Firma aktywnie wykorzystuje narzędzia AI w procesach inżynieryjnych, co może wymagać od kandydata szybkiego dostosowania się do nowych technologii i metod pracy.
🟡
AI tool/connector rollout follows an approved-list and pilot process
Wdrożenie nowych narzędzi AI jest procesem kontrolowanym i wymaga przejścia przez fazę pilotażową, co może oznaczać powolniejsze wprowadzanie innowacji.
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The client is AWS-first overall; for data platform and analytics workloads it also runs GCP, with BigQuery as the primary data warehouse
Firma korzysta z wielu dostawców chmury (AWS i GCP) i różnych narzędzi, co wymaga elastyczności i umiejętności pracy w zróżnicowanym środowisku technologicznym.