Job Description

Our client is a leading slot games provider in the online gambling industry, headquartered in Prague. The company is recognized for creating innovative, high-quality games with engaging mechanics and immersive design, enjoyed by players worldwide. With a strong international presence across Prague, Malta, and Latin America, they continue to set benchmarks in the iGaming market.

Requirements

• 2+ years of experience in Data Engineering / Data Science / Machine Learning.
• Strong Python skills and experience with data processing, automation, and building data services.
• Hands-on experience with ETL/ELT tools and frameworks such as Airflow, dbt, or similar solutions.
• Experience working with REST APIs, including authentication, pagination, error handling, and data integration.
• Strong knowledge of SQL and experience with databases such as MySQL, PostgreSQL, and other relational/non-relational DBMS.
• Experience designing and maintaining scalable data pipelines and infrastructure.
• Experience with data collection, parsing, transformation, cleaning, aggregation, and validation.
• Practical experience developing and improving machine learning models for forecasting, classification, recommendations, anomaly detection, or similar business use cases.
• Strong understanding of predictive modeling and analytical algorithms.
• Experience working with large volumes of structured and unstructured data.
• Ability to monitor data quality, pipeline stability, and optimize performance.
• Strong analytical and problem-solving skills.
• Ability to work effectively with Analytics, Product, Engineering, and Business teams.
• Good technical documentation skills.
• Experience in iGaming or another data-driven industry would be a strong advantage.

Responsibilities:

• Development and maintenance of automated data pipelines using ETL tools and frameworks such as Airflow, dbt, and other data automation solutions
• Writing Python scripts and services for data parsing, scraping, collection, transformation, and integration from various external and internal sources
• Experience working with REST APIs, including data extraction, authentication, pagination, error handling, and integration with internal and external data sources
• Designing, optimizing, and supporting databases including MySQL, PostgreSQL, and other relational/non-relational DBMS
• Building scalable data infrastructure for analytics, reporting, and machine learning projects
• Collecting, aggregating, cleaning, and validating large volumes of structured and unstructured data
• Developing, training, and improving machine learning models for forecasting, classification, recommendation systems, anomaly detection, and other business tasks
• Creating predictive models and analytical algorithms based on historical and real-time data
• Working closely with analytics, product, engineering, and business teams to implement data-driven solutions
• Monitoring data quality, pipeline stability, and performance optimization
• Preparing technical documentation for data flows, models, and infrastructure

Benefits

• Full-time employment
• Opportunity to build a career in a fast-growing international IT company
• Cool office with a friendly international team
• Corporate events and team-building activities
• Multisport card after probation period