Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field. 8+ Experience designing and building scalable data platforms and distributed systems. Strong programming skills in Python and SQL, with proficiency in Java or Scala preferred. Experience with Airflow, Kubeflow, or MLflow to build and orchestrate scalable AI data pipelines. Experience building scalable batch and streaming data pipelines using Spark (PySpark), Kafka, Airflow, and Ray, with proficiency in Pandas and modern data lake/lakehouse architectures (e.g., Iceberg, Delta Lake).
Experience using modern development tools, including AI-assisted coding tools, while applying sound engineering judgment to review, validate, and improve generated code. Knowledge of RAG architectures, embedding generation, vector databases, and AI data preparation for LLMs and agentic AI. Experience with cloud platforms (AWS, Azure, or GCP), Kubernetes, Docker, CI/CD, and Infrastructure as Code. Demonstrated ability to understand complex user workflows, translate them into practical technical solutions, and collaborate across teams to deliver measurable outcomes.
Excellent communication and collaboration skills, with the ability to translate technical concepts into clear, business focused insights.