We are looking for a talented AI Data Engineer to design, build, and optimize scalable data pipelines and AI/ML data solutions. You will work with engineering and data science teams to transform complex datasets into reliable, production-ready data systems that power AI and machine learning applications.

Key Responsibilities

Design and develop scalable data pipelines and ETL/ELT workflows.
Build and optimize data processing solutions using Python and SQL.
Prepare, clean, transform, and validate large datasets for AI/ML applications.
Collaborate with Data Scientists and ML Engineers to support model development and deployment.
Develop data infrastructure for machine learning and AI workloads.
Optimize data quality, performance, reliability, and scalability.
Work with cloud-based data platforms and services.
Implement monitoring, testing, documentation, and data governance best practices.

Required Skills

2–8 years of experience in Data Engineering, AI/ML Engineering, or a related field.

Strong Python programming skills.
Advanced SQL and database concepts.
Understanding of Machine Learning and AI data workflows.
Experience with at least one major cloud platform: AWS, Azure, or Google Cloud.
Strong knowledge of data pipelines, ETL/ELT, data modeling, and distributed data processing.
Strong analytical and problem-solving skills.

Preferred Qualifications

Experience with Spark, Databricks, Snowflake, Airflow, Kafka, or similar technologies.
Experience working with ML/AI platforms and large-scale datasets.
Knowledge of MLOps, Docker, Kubernetes, or CI/CD.
Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.