At PayDepot we build several B2B and B2C fintech products, including payment infrastructure, crypto services and financial platforms. We are growing rapidly and are looking for a Data Analyst / Analytics Engineer who will help us turn data into actionable insights and improve the way our teams work with data.
This is a hands-on role combining data analysis, SQL, reporting and data automation. You will work closely with Product, Engineering and Business teams and gradually take ownership of data pipelines, models and reporting workflows.
What you will do
- Design, build and maintain data pipelines from raw data to BI
- Build and maintain data models and data marts
- Monitor data quality, consistency and integrity across systems
- Work closely with Product, Engineering and Business teams to define analytics requirements
- Automate recurring reporting and data workflows
What we expect
- 2+ years of experience in Data Analytics, BI, Data Engineering or a similar role
- Strong SQL knowledge, familiarity with Postgres & Redshift is a plus
- Sufficient Python knowledge for data processing and automation
- Understanding of data modelling and data warehouse concepts
- Experience working with data pipelines or automated data workflows
- Strong analytical thinking and attention to detail
- Ability to work independently and communicate clearly with different teams
- Fluent English
Nice to have
- Experience with ETL/ELT tools or frameworks
- Experience with dbt, Airflow or similar tools
- Experience with cloud data platforms such as AWS, GCP or Azure
- Experience in fintech, banking, payments or crypto products
- Experience with product analytics and event-based data
- Experience improving data quality and reporting processes
- STEM degree or equivalent technical background
What we offer
- Full relocation support and working visa
- Competitive salary based on experience
- Modern office in Limassol
- Flexible days off when you need them
What awaits you
- Working in a small and fast-paced Scrum team
- A practical role where you can influence how we work with data
- No bureaucracy - we focus on practical solutions and common sense
- Pleasant colleagues and a healthy internal culture
- A non-toxic environment with respect for work-life balance (we turn off Slack during vacations)
