Middle Data Engineer

Dataforest is looking for a Middle Data Engineer to join our team and work on the Dropship project — a cutting-edge data intelligence platform for e-commerce analytics.
You will be responsible for developing and maintaining a scalable data architecture that powers large-scale data collection, processing, analysis, and integrations.

If you are passionate about data optimization, system performance, and architecture, we’re waiting for your CV!
 

     Requirements:

• 2+ years of commercial experience with Python.
• Advanced experience with SQL DBs (optimisations, monitoring, etc.);
• PostgreSQL — must have;
• Solid understanding of ETL principles (architecture/ monitoring/ alerting/search and resolve bottlenecks);
• Experience with Message brokers: Kafka/ Redis;
• Experience with Pandas;
• Familiar with AWS infrastructure (boto3, S3 buckets, etc);
• Experience working with large volumes of data;
• Understanding the principles of medallion architecture.
   

     Will Be a Plus:

• Understanding noSQL DBs (Elastic);
• TimeScaleDB;
• PySpark;
• Experience with e-commerce or fin-tech.
   

     Key Responsibilities:

• Develop and maintain a robust and scalable data processing architecture using Python.
• Design, optimize, and monitor data pipelines using Kafka and AWS SQS.
• Implement and optimize ETL processes for various data sources.
• Manage and optimize SQL and NoSQL databases (PostgreSQL, TimeScaleDB, Elasticsearch).
• Work with AWS infrastructure to ensure reliability, scalability, and cost efficiency.

• Proactively identify bottlenecks and suggest technical improvements.
   

  We offer:

• Working in a fast growing company;
• Great networking opportunities with international clients, challenging tasks;
• Personal and professional development opportunities;
• Competitive salary fixed in USD;
• Paid vacation and sick leaves;
• Flexible work schedule;
• Friendly working environment with minimal hierarchy;
• Team building activities, corporate events.