payabl

Senior Data Analyst

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MidHybryda·KrakówFull-time

#447762·Dodano 24 dni temu·2

Źródło: payabl.

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Tech Stack / Keywords

SQL Python pandasMatplotlibPlotlySeabornSciPyPostgreSQLApache DruidApache Superset

Firma i stanowisko

payabl. empowers businesses to grow through payments innovation and banking services. It is a licensed financial company with principal membership with card schemes, specializing in global payments and providing businesses with multi-currency accounts via its platform payabl.one.

Wymagania

Strong SQL skills including window functions, CTEs, and aggregation logic with performance reasoning.
Proficient in Python for analysis with libraries such as pandas, Matplotlib, Plotly, Seaborn, SciPy or equivalent.
Experience with relational and analytical databases including PostgreSQL; exposure to columnar or OLAP engines such as Apache Druid, ClickHouse, or BigQuery is a plus.
Experience building dashboards in BI tools like Apache Superset, Metabase, Power BI, Tableau, Looker, or Qlik.
Comfortable working with notebooks (e.g., JupyterHub, Jupyter) for exploratory analysis and reporting.
Familiarity with Git-based workflows for version control and code reviews.
Ability to automate data reports ensuring efficiency and accuracy.
Excellent communication skills for presenting analysis to various audiences including senior decision makers.
Strong sense of ownership and end-to-end responsibility.

Nice to have:

Experience in fintech/payments and understanding of transactional data including chargebacks, fees, interchange, acquiring, and settlement.
Experience with regulatory or scheme reporting (card schemes, PSD2, AML).
Experience with dbt for models, tests, documentation.
Basic understanding of Apache Airflow and pipeline debugging.
Familiarity with scheduling and automatic report generation (cron, Airflow, jupyter_scheduler).
Knowledge of event tracking, product analytics tools (Amplitude, Google Analytics, Matomo).
Practical use of AI tools (LLM-assisted coding, querying, summarizing).
Exposure to machine learning for business problems like forecasting, anomaly detection, segmentation, fraud, or risk scoring.

Obowiązki

Investigate payment performance issues across gateways, issuers, and merchants, explaining causes.
Prepare datasets for analysis by filtering, handling missing values, and validating quality.
Apply statistical techniques to identify patterns and quantify changes.
Build and maintain Superset dashboards and Druid data cubes.
Prepare recurring reports for internal and regulatory stakeholders ensuring accuracy and timely delivery.
Automate recurring analysis and reporting.
Present insights and recommendations clearly to stakeholders.
Collaborate with other departments to understand data needs and translate business questions into analytical queries.

Benefity

Provident Fund contributions after probation.
Annual Learning Budget for professional development (after probation).
€150 monthly Wolt allowance.
SportsBenefits membership for gym and sports facilities.
Potential eligibility for a company car after one year.
Complimentary parking space near the office.
25 days vacation plus public holidays and 10 sick days.
Exclusive local discount card and tickets for events.
Free Greek language classes twice a week.
Company celebrations and global collaboration opportunities.

Opieka zdrowotna

Karta sportowa

Parking dla aut

Płatny urlop

Kursy językowe

Spotkania integracyjne

Dofinansowanie szkoleń

Budżet konferencyjny

payabl

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