Data Engineer / Data Scientist

Build and maintain scalable data pipelines, ML models, and analytics for an iGaming/Web3 company using Python, cloud platforms, and AI to drive player engagement and fraud detection.

Compensation

€50K–€80K / yr

Location

Europe

Work setup

Remote

Seniority

Not specified

Employment

Full time

Experience

2+ years

Skills

agentic-ai
ai
airflow
analytics
aws
azure
bigquery
blockchain
business-intelligence
cloud
data-engineering
data-lake
data-modeling
data-pipelines
data-quality
data-science
docker
elt
etl
feature-engineering
gcp
generative-ai
git
kafka
kubernetes
llm
looker
machine-learning
mlflow
mlops
model-evaluation
numpy
pandas
postgresql
powerbi
python
pytorch
rabbitmq
recommendation-systems
redshift
scikit-learn
snowflake
spark
sql
tableau
tensorflow
web3

Full description

Phoenix Games is a technology company building next-generation iGaming and Web3 products for a global audience. We leverage AI, cloud technologies, blockchain, and advanced analytics to create intelligent, data-driven gaming experiences.
As we continue to scale, we're looking for Data Engineer / Data Scientist to help us build modern data infrastructure, develop machine learning solutions, and turn massive volumes of data into actionable insights.

What You'll Do
Design, build, and maintain scalable data pipelines and ETL/ELT processes.
Develop and optimize data warehouses and data lake architectures.
Collect, clean, and transform large datasets from multiple sources.
Build predictive models, recommendation systems, and analytical solutions.
Apply machine learning techniques to improve player engagement, fraud detection, personalization, and business intelligence.
Design dashboards and reporting solutions for business stakeholders.
Collaborate with Product Managers, Engineers, and BI teams to define data-driven strategies.
Optimize data processing performance and ensure data quality.
Implement monitoring, validation, and governance for data pipelines.
Research and evaluate new AI and machine learning technologies.

Tech Stack
Python
SQL
PostgreSQL
Snowflake / BigQuery / Redshift
Apache Airflow
Spark
Pandas
NumPy
Scikit-learn
TensorFlow / PyTorch
MLflow
Docker
Kubernetes
AWS / Azure / GCP
Git
Power BI / Looker / Tableau

Requirements
2+ years of commercial experience in Data Engineering, Data Science, or Machine Learning.
Strong Python programming skills.
Advanced SQL knowledge.
Experience building scalable data pipelines.
Experience with cloud data platforms.
Strong understanding of data modeling and database design.
Experience with machine learning algorithms and model evaluation.
Experience working with large datasets.
Familiarity with Docker and cloud environments.
Strong analytical and problem-solving skills.
Upper-Intermediate English or higher.

Nice to Have
Experience with LLMs, Generative AI, or AI agents.Knowledge of real-time data streaming (Kafka, RabbitMQ).