Description

Design and maintain scalable data platforms, pipelines, and architectures to support analytics, machine learning, and GenAI use cases.

This role is on-site.

Responsibilities

• Architect scalable data lakes, warehouses, and real-time streaming solutions on Azure, AWS, or GCP.
• Develop and maintain ETL/ELT processes and data integration frameworks using Python and Spark.
• Deploy AI/ML models into production and implement MLOps and DataOps best practices.
• Define and enforce data governance, security, privacy, and compliance standards.
• Optimize platform performance, scalability, and cost efficiency while integrating emerging AI technologies.

Required Skills

• 5+ years of experience in Data Engineering and Data Architecture.
• Strong proficiency in Python, SQL, Spark, and Databricks.
• Hands-on experience with Machine Learning, Generative AI, and MLOps tools.
• Experience with orchestration tools such as Airflow or Azure Data Factory.
• Knowledge of data lakes, data warehouses, and big data technologies.
• Understanding of APIs, microservices, and containerization (Docker, Kubernetes).
• Bachelor's degree in Computer Science or related field.

Key Skills

Education

Bachelor's degree