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описание
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.
задачи
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.
требования
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.
условия
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;
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