Machine Learning Data Engineer

Data Engineering: Strong experience with Hadoop ecosystem (Hive, Impala, Spark, Kafka,

. Iceberg, Ranger, Atlas), Teradata and data pipeline orchestration.

. Full Stack Development: Proficiency in Python, Shell scripting, REST APIs, and web

frameworks (Flask, React, etc.).

. Machine Learning & AI: Hands-on experience with ML platforms (CML), Spark MLlib,

. Python ML libraries (scikit-learn, XGBoost), and model deployment.

. GenAI/LLM Applications: Familiarity with building applications using large language models

. (e.g., OpenAI, Hugging Face, LangChain) for enterprise use cases.

. Security & Governance: Experience with enterprise data security (LDAP, Kerberos, RBAC), data masking, and access control.

. Performance Tuning: Proven ability to optimize data applications and queries in large-scale environments (Hadoop, Teradata).

. Tools & Platforms: Cloudera Data Platform (CDP), Informatica, QlikSense, Apache Oozie,

Git, CI/CD pipelines.

. Soft Skills: Strong analytical and problem-solving skills, excellent communication, and ability

to work in cross-functional teams.