Data Engineer

• →Design and develop efficient data pipelines using Python, AWS Glue/pyspark, AWS Lambda, Kafka, and related technologies.
• →Implement and optimize ETL processes for data extraction, transformation, and loading into relational databases, especially Postgres.
• →Collaborate on data warehouse architectures, ensuring proper data modeling, storage, and access.
• →Utilize tools like StitchData and Apache Hudi for data integration and incremental management, improving efficiency and enabling complex operations.
• →Identify and resolve data quality and consistency issues, implementing monitoring processes across pipelines and storage systems.

• Strong Python skills and proficiency in associated libraries for data processing and manipulation.
• Expertise in AWS Glue/pyspark, AWS Lambda, and Kafka for ETL workflow development and streaming architecture.
• Experience in designing and implementing relational databases, specifically Postgres.
• Practical knowledge of data pipeline development, ETL processes, and data warehouses.
• Familiarity with data integration tools like StitchData and Apache Hudi for efficient incremental data management.
• Advanced level of English for effective communication and collaboration.

Benefits:

• Competitive salary.
• Annual offsite team trip.
• Learn from a very high performing team.
• Training from US mentors.

If you're a passionate Data Engineer with experience in these technologies and seek a stimulating and challenging environment, join our team and contribute to the success of our advanced data processing and management solutions!