Senior Data Engineer

14 января 2020    30
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Job Summary
We are looking for a Senior Data Engineer who will participate in refactoring, redesigning, and improving the data platform, as well as participate in the development of new projects.

Requirements:
— 5+ years of experience in Data Engineering/Software Engineering/Database Development
— Strong understanding of business, customer, product, and clickstream analytics, recommendations and personalization, A/B testing
— Database proficiency: experience with both relational and NoSQL databases
— Understanding of ETL and data curation
— Hands-on experience working with large data sets
— Proficiency with Scala and Java (and JVM ecosystem in general)
— Strong understanding and experience:
— MapReduce systems: Hive, Hadoop
— Spark, Spark SQL, and Spark Streaming
— Kafka ecosystem (Kafka Connect / Kafka Streams)
— Workflow/job scheduling systems (Apache Airflow)
— Distributed query execution engines (e.g., Presto)
— Service-based architectures and containerization
— AWS (EMR, S3)
— CI/CD
— Upper-Intermediate English level

Preferable:
— Database/Data Warehousing background

We offer multiple benefits, such as:
— Challenging work in an international and professional environment
— Mastering the English language with a native speaker
— 40-hour working week with flexible working hours
— Flexible WFH policy
— Competitive salary
— PE accounting and support
— 20 paid vacation days per year
— 14 paid sick leave days per year
— Medical insurance
— Annual 250$ deposit for attending external events (conferences, workshops, etc.)
— Long-term employment and real opportunities to change roles and projects within the company
— Yoga classes, workout corner
— Collaborative and friendly team environment
— Cozy, fully equipped office space in the city center (near “Palats Ukraina” subway station)

Responsibilities:
— Work with the Data Engineering team to refactor, redesign, and improve the data platform
— Support architectural initiatives to improve reliability, resiliency, stability, and data quality
— Participate in the development of new projects
— Build ETL pipelines using Kafka/Spark/Hive
— Monitor the health of our system and optimize for performance and cost savings
— Support daily ETL jobs monitoring and participate in correcting any issues that arise
— Develop unit and integration tests

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