Middle/Senior Data Engineer (Social Shopping Platform)

We are seeking a motivated and self-driven individual to join our dynamic team. Our team highly values employees' freedom, independence in decision-making, and desire to deeply understand clients' requests and identify the root of the problem. We believe that people who embrace this mindset are destined to succeed as acclaimed professionals and driving forces in data development in Ukraine. 

CUSTOMER
Our Client is a community-powered fashion marketplace with over 30 million registered users across more than 150+ countries. It's a platform for discovering and celebrating personal style while promoting sustainable fashion by extending the life of millions of garments. Founded in 2011 and headquartered in London, with offices in Manchester and New York, our Client employs around 400 people.

• Contributing to new technology investigations and complex solution design, supporting a culture of innovation by considering matters of security, scalability, and reliability, with a focus on building out our ETL processes 
• Working with a modern data stack, coming up with well-designed technical solutions and robust code, and implementing data governance processes 
• Working and professionally communicating with the customer’s team 
• Taking responsibility for delivering major solution features 
• Participating in the requirements gathering and clarification process, proposing optimal architecture strategies, and leading the data architecture implementation 
• Developing core modules and functions, designing scalable and cost-effective solutions 
• Performing code reviews, writing unit and integration tests 
• Scaling the distributed system and infrastructure to the next level 
• Building data platform using power of AWS cloud provider 

• 3+ years of strong experience with Python as a programming language for data pipelines and related tools
• Proven strong track record of building data platforms and managing infrastructure for Airflow and Databricks
• Familiarity and understanding of distributed data processing with Spark for data pipeline optimization and monitoring workloads
• Proven strong track record of building data transformations using data build tools 
• Excellent implementation of data modeling and data warehousing best practices
• Good written and spoken English communication skills 
• Familiarity with software engineering best practices: testing, PRs, Git, code reviews, code design, releasing 
• Proven strong track record of building data platforms and managing infrastructure for Airflow and Databricks 

WOULD BE A PLUS

• Strong Data Domain background – understanding of how data engineers, data scientists, analytics engineers, and analysts work to be able to work closely with them and understand their needs 
• Experience with DAGs and orchestration tools 
• Experience in developing event-driven data pipelines