- 4+ years of experience across Data Engineering and AI/ML engineering in production environments.
- Strong programming skills in Python and SQL, with hands-on expertise in Spark/PySpark for large-scale data processing.
- Deep experience with cloud platforms (Azure or AWS), including services for data engineering, ML, and distributed systems (e.g., Databricks, Synapse, EMR, S3, ADF, etc.).
- Hands-on experience in building and deploying scalable data pipelines and ML systems.
- Solid understanding of data modeling (data lakes, lakehouse, warehouse, medallion architecture).
- Experience with MLOps frameworks (e.g., MLflow) and production model lifecycle management.
- Practical experience with LLMs / Generative AI applications, including RAG, document processing, or workflow automation.
- Experience with containerization (Docker) and orchestration (Kubernetes).
- Strong understanding of system design, scalability, and cost optimization in cloud environments.
- Experience with data quality, observability, and monitoring frameworks.
- Ability to translate business problems into scalable technical solutions with measurable impact.