Data Engineer (AI/ML)

About the role

We are looking for a Data Engineer (AI/ML) to own the end‑to‑end data pipelines that feed our analytics, finance and AI systems. You will ingest data from external APIs, build dbt models, orchestrate workflows with Apache Airflow and take machine‑learning and LLM solutions from prototype to production, directly influencing daily business decisions.

Key responsibilities

• Design and implement Python‑based ingestion pipelines from REST APIs and cloud sources.
• Develop, test and document dbt models that transform raw data into trusted data marts.
• Create and maintain Apache Airflow DAGs for automated reporting, inventory and data extraction.
• Build, evaluate and monitor machine‑learning models for forecasting, classification and anomaly detection.
• Deploy production‑grade agentic AI pipelines that act on live business data.
• Implement data‑quality validation, automated testing and monitoring for pipelines and models.
• Document schemas, features, model behavior and integration details.
• Mentor junior engineers through code reviews and pairing.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Data Engineering or a related field.
• 3+ years of professional experience in Python‑based data engineering, ML engineering or backend data work.
• Proven ownership of production pipelines from API research to downstream validation.
• Strong problem‑solving skills for handling third‑party API integration challenges.

Required skills

• Python
• REST API integration
• dbt (models, tests, documentation)
• Apache Airflow (DAG authoring, dependency management)
• SQL
• Machine learning model development and monitoring
• LLM‑based solutions
• Data quality validation and automated testing