Advanced Python Engineering: Develop high-efficiency, Object-Oriented (OOP) analytical tools and frameworks for processing large-scale financial data.
Complex Data Modeling: Architect and manage sophisticated data structures, transforming nested, multi-source payment data into optimized tabular formats.
SQL Optimization: Write and tune expert-level SQL (PostgreSQL/Redshift) for complex joins and high-volume analytical queries.
Pipeline Orchestration: Design and maintain scalable ETL/ELT workflows using Apache Airflow within the AWS ecosystem.
Code Architecture: Ensure analytical codebases are modular, scalable, and maintainable using Git and best development practices.
Real-Time Analytics: Build logic for real-time processing to support instantaneous fraud detection and payment scheme analysis.

Languages: Fluency in SQL (Postgres/Redshift) and Python (focus on OOP and efficiency).
Tools: Experience with Apache Airflow, Git, and the AWS ecosystem.
Domain: Interest or experience in FinTech and real-time processing.
Mindset: Strong critical thinking, attention to detail, and ability to manage multiple tasks.
Experience: 3+ years in a data-focused role.

```
      Spacious and modern office;
```
Paid lunch in the office;
Company sponsored professional trainings, certifications, and conferences;
Social events
team buildings, corporate events;
Friendly and experienced team members who will support your professional growth.

Senior Data Analyst

Key skills