Pytohon Data Engineer (Dataricks, AWS, LLM)

This position is very urgent! I would be happy to have a call with you today and give all the details.
 

Location: Remote
Employment Type: Full-time
Contract Duration: 6 months (with possibility of extension)
 

About Us

We are a SaaS company that collects and analyzes large-scale web data to generate actionable consumer insights for global brands. Our platform powers dashboards and data deliveries built on a classified catalog of products, reviews, and social content (posts, videos, and more).

We work with high-volume, complex datasets and modern data technologies. Collaboration, continuous learning, and a strong problem-solving mindset are core to our culture.

Role Overview

We are looking for a Senior Software Data Engineer to design, build, and optimize scalable, production-grade data pipelines using AWS and Databricks.

As a key member of the Data Team, you will be responsible for ensuring data reliability, integrity, and performance. You will also contribute to ML, MLflow, and LLM-based workflows, delivering high-quality, client-ready data solutions on time.

You will collaborate closely with R&D, Product, and Delivery teams to validate features, resolve issues, and ensure smooth, reliable delivery of insights to clients.

Responsibilities

• Design, build, and maintain scalable data pipelines using PySpark, Python, and AWS services
• Deliver production-ready data outputs with high accuracy, reliability, and timeliness
• Optimize data processing performance and troubleshoot complex pipeline issues
• Develop and enhance automated testing and data quality frameworks
• Integrate ML, MLflow, and LLM-based workflows into existing pipelines
• Collaborate with Product Managers and Delivery Analysts to define release readiness and client-facing quality standards

• Promote best practices in data engineering, QA, documentation, and maintainable code

   

Requirements

• 5+ years of experience as a Data Engineer in production environments
• Strong expertise in PySpark, Python, and SQL
• Hands-on experience with AWS (data services and cloud infrastructure)
• Experience working with Databricks / DBX framework
• Solid background in automated testing and QA for data pipelines
• Proven problem-solving and debugging skills, including pipeline optimization

• Excellent English communication skills and ability to work cross-functionally in distributed teams

   

Nice to Have / Advantages

• Experience with big data architectures and data lakes
• Familiarity with CI/CD pipelines and DevOps practices
• Experience with MLflow and exposure to LLM-based solutions

• Knowledge of data governance, monitoring, and observability frameworks

   

Why Join Us

• Work on high-impact data challenges that directly influence client outcomes
• Be part of a collaborative team building data and AI-powered solutions
• Fully remote work environment with flexible setup
• Competitive compensation and opportunity for contract extension