Description

Key Skills: Java, SQL, Python, Data Engineering, Kafka, Airflow, Storage, Automation, Testing

Roles and Responsibilities:

• Build and maintain high-performance streaming and batch data pipelines with reliable low-latency ingestion and high-throughput processing.
• Implement and extend embedding generation workflows, vector store integrations, and retrieval pipelines for semantic search and RAG systems.
• Embed end-to-end observability into data systems, including metrics, structured logging, automated alerts, drift detection, and failure analysis.
• Implement data quality validation, schema evolution safeguards, and governance/compliance controls.
• Drive execution across the full development lifecycle: prototyping, implementation, testing, deployment, optimization, and documentation.
• Collaborate with infrastructure, ML engineering, product, and governance teams to deliver production-ready AI capabilities.

Skills Required:

• 4+ years of data engineering experience, including at least 1 year in a lead or senior technical role.
• Experience building and scaling streaming data pipelines in large-scale, distributed environments.
• Strong skills in Python, Java, and SQL (expert level in either Python or Java).
• Proven experience building streaming data pipelines (e.g., Kafka).
• Experience with embedding pipelines and vector stores.
• Hands-on experience with workflow orchestration tools (Airflow).

Education: Bachelor's Degree in related field

Key Skills

Education

Any Graduate