Data Engineer

Required Experience

• 3-5 years of professional IT/Data Engineering experience.
• At least 2 years of strong hands-on experience with Python and SQL.
• Meaningful hands-on experience with Apache Spark/PySpark.
• Production experience with Databricks is strongly preferred.
• Practical experience with AWS or Azure or GCP data services is required.
• Experience developing production ETL/ELT pipelines.
• Experience working with large datasets and distributed data-processing systems.
• Exposure to production support and troubleshooting.

The ideal candidate should:

• Be a strong hands-on engineer rather than someone with only theoretical knowledge.
• Be comfortable switching between Databricks and AWS/Azure/GCP-oriented projects.
• Be able to understand an existing architecture and independently implement assigned components.
• Have strong debugging and problem-solving skills.
• Be comfortable learning unfamiliar technologies when required by a project.
• Have good communication skills for interaction with customers, architects, leads, and internal teams.
• Be capable of explaining technical decisions and implementation approaches.
• Write clean, maintainable, reusable, and testable code.
  Understand production reliability, security, scalability, and maintainability considerations.

The preferred candidate should have the following core combination:
Python + SQL + PySpark/Spark + Databricks + AWS/Azure/GCP + ETL/ELT

Candidates with additional exposure to:
Kafka + Airflow/Composer + BigQuery + FastAPI + Docker/GKE + dbt + AI/LLM integration

Education
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent relevant professional experience.