Data Engineer

SmartCat is an AI-driven company that tackles complex data challenges with innovative solutions and delivers measurable positive impacts on businesses, everyday life, and society.

• Design, build, and maintain scalable data pipelines using Apache Spark and modern data platforms;
• Develop and optimize data lakehouse architectures for data analytics and machine learning workflows;
• Implement data models and structures that ensure data quality, consistency, and accessibility;
• Collaborate with data scientists and analysts to understand data requirements and deliver solutions;
• Help ensure data security and compliance with relevant regulations;
• Monitor and troubleshoot data pipeline performance and reliability;
• Continuously improve data engineering processes and best practices;
• Collaborate with cross-functional teams and contribute to technical discussions;
• Provide technical guidance and mentor junior engineers at the Senior level.

• Experience with Python or Scala/Java;
• Advanced knowledge of SQL;
• Hands-on experience with Apache Spark, Databricks, Snowflake, or Microsoft Fabric;
• Understanding of data lakehouse concepts and architecture;
• Understanding of distributed systems fundamentals;
• Data modeling and data warehousing skills;
• Experience with cloud-native data architectures on AWS, Azure, or GCP;
• Enjoy learning new things and trying different solutions;
• Value a healthy work-life balance and avoid overtime;
• Know when and how to ask for help and work collaboratively as part of a team;
• Nice to have: Kafka, Flink, or similar streaming technologies, Kubernetes, Machine Learning.

• Loyalty coefficient: 10% on net compensation after 3 years at SmartCat and 20% after 5 years;
• Knowledge budget;
• Flexible working hours;
• Transparent pay grades from L1 to L10, career path, salary, strategy, and financial reports;
• Full support towards gaining expertise.