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 databases — including optimization, monitoring, and performance tuning.
• PostgreSQL — must have.
• Solid understanding of ETL principles and best practices.
• Strong knowledge of algorithms and cyclomatic complexity, with the ability to design efficient, scalable data logic.
• Experience with Linux environments, cloud services (AWS: boto3, Lambda, S3, SQS, ECS), and Docker.
• Familiarity with message brokers.
• Experience with Pandas and NumPy for data processing and analysis.
• Understanding of system architecture and monitoring (logs, metrics, Prometheus, Grafana).
• Excellent problem-solving and communication skills, with the ability to work both independently and collaboratively.
   

     Will Be a Plus:

• Experience in web scraping, data extraction, cleaning, and visualization.
• Understanding of NoSQL databases — ideally, Elasticsearch (not only as part of ready-made logging tools like LogStash or FileBeat).
• Experience with multiprocessing and multithreading.
• Familiarity with Flask / Flask-RESTful for API development.
• Experience with Kafka pipelines and stream processing.
• Strong skills in code optimization and structuring.
• TimeScaleDB — good to have.
   

     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.
• Build monitoring and alerting for data systems (Prometheus, Grafana, logs, metrics).
• Collaborate with cross-functional teams, participate in code reviews, and contribute to continuous improvement.

• 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.