Position: Data Engineer (Python), Data Warehouse
Company: DataArt
Category: Data Science
Experience required: 5y
English level: intermediate
Published: 2021-11-01T00:00:00+02:00

About the vacancy

Our client is a travel accessories company creating top-quality suitcases and bags. They seek to make travelling easier and enhance the whole experience. They are expanding the team to build a Data warehouse.

We hire people not for a project but for the company. If the project (or your work on it) is over you go to another project or to a paid “Idle.”

Responsibilities
- Design, run, and maintain scalable data pipelines and related data warehouse for client's e-commerce platform, ERP, 3PLs and their 3rd party services
- Partner with designers, product managers, and engineers to ensure the system is robust and dependable
- Mentor your colleagues and help them through the process, including code reviews
- Catch bugs and monitor data quality so that the production data is accurate and accessible to key stakeholders and business processes
- Review and upgrade client's technology, data structures, and practices

Must have
- 5+ years of software development experience
- 4+ years of experience building data pipelines with Python
- 4+ years of experience with distributed data storage systems/formats & data stores like Snowflake or Redshift (or other Big data systems)
- 2+ years of experience building Kafka based pipelines to stream messages with good exposure to handling failure scenarios
- Proficiency in MS Dynamics
- Excellent understanding of relational databases, including SQL
- Ability to work with and process large datasets
- Familiarity with batch processing/real-time systems using technologies such as Spark, MapReduce, NoSQL, Hive, etc.
- Strong knowledge of Java or Groovy
- Prior experience with a major cloud provider such as AWS or Azure
- Ability to work independently and come up with thoughts to improve processes
- Good spoken English

Would be a plus
- Proficiency in Linux/Unix
- Experience with Scala and Airflow
- Exposure to Continuous Integration/Continuous Deployment & Test Driven Development

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