Description

You will design and maintain secure, scalable ML infrastructure and data pipelines.

Responsibilities

• Design, implement, and maintain secure ETL pipelines for large-scale data processing.
• Develop and optimize data pipelines using Apache Airflow for scheduling and orchestration.
• Work with Kafka/MQTT for real-time data ingestion and processing.
• Manage time-series and telemetry data storage with InfluxDB/TimescaleDB.
• Integrate and manage MLFlow for model tracking, experiment management, and deployment.

Required Skills

• 5-7 years of experience as a Data Engineer or ML Engineer.
• Proficiency in Python, SQL, and Pandas for data analysis and processing.
• Strong hands-on experience with Kafka/MQTT for real-time data streaming.
• Expertise in ETL Pipelines and secure data handling, including encryption and data signing.
• Experience with Apache Airflow for workflow orchestration.
• Familiarity with MLFlow integration for ML lifecycle management.
• Strong understanding of telemetry storage and processing.
• Experience with AWS, GCP, or Azure for cloud data platforms.

Key Skills

Education

Any Graduate