Data Engineer

• Practical experience integrating AI and Large Language Models (LLMs) into data platforms and workflows
• Leveraging AI technologies to enhance data quality and observability
• Automating repetitive processes

What the responsibilities are of the right candidate:

• Build and support enterprise-grade production systems
• Optimize batch/streaming data pipelines
• Integrate AI and LLMs into data platforms
• Enhance data quality and automate processes

Overview: We are seeking a skilled professional to build and support enterprise-grade production systems. The ideal candidate will have strong hands-on skills in PySpark, Python, and SQL, with experience in building, operating, and optimizing data pipelines. Additionally, candidates with application engineering experience should have proficiency in building APIs using FastAPI or Flask and possess robust data modeling skills. Experience integrating AI and LLMs into workflows to enhance data quality and automate processes is highly desirable.

Job Must Haves:

• Strong hands-on skills in PySpark, Python, and SQL
• Databricks
• AWS
• Experience building, operating, and optimizing batch/streaming data pipelines
• Experience with data quality checks and performance tuning in production
• Experience building APIs and backend services using FastAPI or Flask
• Strong data modeling skills (e.g., Pydantic)
• Experience with event-driven architectures, concurrency/async processing, database integration, testing, CI/CD, containers, and production observability