Description

You will build and optimize large-scale data processing pipelines and scalable data platforms to support machine learning products.

Responsibilities

• Design, build, and maintain scalable ETL/ELT workflows and data pipelines for machine learning initiatives.
• Partner with Data Science and ML Engineering teams to prepare and serve high-quality datasets for modeling and inference.
• Process structured and unstructured data at scale using big data technologies.
• Develop and optimize data architectures for performance, reliability, and security.
• Automate data workflows and support CI/CD for both data and ML pipelines.
• Identify data quality issues and implement solutions to ensure integrity.
• Contribute to model deployment workflows and integration into business applications.

Required Skills

• 10+ years of professional experience in Data Engineering.
• Strong programming skills in Python, Scala, or Java.
• Hands-on experience with Apache Spark, Hadoop, Kafka, or similar big data technologies.
• Solid experience in SQL and relational database systems.
• Experience supporting ML workflows, including data preparation, feature engineering, and model integration.
• Familiarity with cloud platforms such as GCP, AWS, or Azure.
• Working knowledge of CI/CD, Git, and infrastructure-as-code tools.
• Strong understanding of data warehousing concepts and tools like BigQuery, Snowflake, or Redshift.

Preferred Skills

• Experience with MLflow, Kubeflow, or similar ML orchestration tools.
• Familiarity with containerization and orchestration using Docker or Kubernetes.
• Prior experience in retail or eCommerce domains.
• Knowledge of data privacy and compliance best practices.

Key Skills

Education

Any Gradute