Junior Payment Data Analyst (Remote)

Job Overview

The Junior Payment Data Analyst will work with payment information across the Pay2Kiss ecosystem, contribute to data pipelines, build automated monitoring and BI reporting, improve data quality, and perform analyses that support payment and business decisions.

Key Responsibilities

• Work with payment data and contribute to building and maintaining data pipelines from raw data through OBT.
• Integrate data from payment service providers, processing systems, and product events.
• Develop automated monitoring for important payment and business metrics.
• Build BI reporting and alerting designed to operate without manual intervention.
• Implement automated checks for data completeness, freshness, and accuracy.
• Identify and resolve inconsistencies within payment and analytical data.
• Conduct analytical research, prepare relevant datasets, and develop conclusions that help the team make decisions.
• Collaborate with the payment team, data analysts, and data engineers.
• Process analytical requests and align teams on metric definitions and data logic.
• Help establish a shared understanding of payment data across collaborating teams.

Required Qualifications

• At least 1 year of commercial Data Analytics experience.
• Strong SQL skills, including window functions, aggregations, and working with large datasets.
• Basic Python knowledge for data analysis and automation of routine tasks.
• Experience with at least one BI tool such as Tableau, Power BI, Looker, or Metabase.
• Understanding of key B2C product metrics including conversion, funnel performance, retention, churn, LTV, and CAC.
• Interest in AI tools and experience using them to automate routine work.
• Strong attention to detail, curiosity, and a proactive working style.
• Openness to feedback and willingness to take ownership of assigned work.

Preferred Qualifications

• Experience with dbt, Databricks, data warehouses, or other components of a modern data stack.
• Experience in payment analytics or understanding of payment processes and metrics.
• Familiarity with payment metrics and concepts including approval rate, chargebacks, refunds, fraud prevention, routing, and retry strategies.

Data & Analytics Stack

• SQL
• Python
• Tableau, Power BI, Looker, or Metabase
• dbt
• Databricks
• Data warehouses
• Data pipelines
• Business intelligence reporting
• Automated monitoring and alerting
• Claude Code and other AI tools

Payment Analytics Focus

The role supports Pay2Kiss, Kiss My Apps’ payment ecosystem. You will work with data originating from payment service providers, processing systems, and product events while helping improve the analytics infrastructure supporting payment operations.

Relevant payment concepts include approval rates, chargebacks, refunds, fraud prevention, routing, and retry strategies. Experience in these areas is considered a plus rather than a mandatory qualification.

Remote Work & Equipment

The listing identifies the position as remote and states that employees can choose a fully remote arrangement from anywhere in the “free world.” Kiss My Apps also provides optional access to offices in Kyiv and Warsaw.

The company states that employees are provided with the equipment needed for work regardless of their work arrangement or geography. The supplied listing does not provide a specific list of eligible countries or required time zones.

Development & Benefits

• Internal English speaking clubs with a native speaker.
• Opportunities to participate in internal and external events.
• Annual professional-development budget covering up to 50% of professional conferences, educational events, and related activities.
• Annual flexible benefits budget that can be allocated toward 50% of medical insurance, psychotherapy, sports, or dental expenses.
• 40 days of paid vacation and sick leave without fixed date restrictions.
• Online yoga sessions twice per week.
• Opportunities to develop in both Data Analytics and Analytics Engineering.

Hiring Process

• Introductory conversation with a recruiter.
• Test assignment.
• Technical interview with the Data Analytics Lead and Head of Analytics.
• Final interview with the Head of Payment.