Description

You will build and maintain data pipelines while deploying machine learning models and generative AI solutions. This role is on-site.

Responsibilities

• Develop scalable data engineering workflows using Python, PySpark, and SQL.
• Design and manage data infrastructure on AWS Services, Azure Databricks, and Snowflake.
• Implement MLOps practices to deploy and monitor Machine Learning and Gen AI models.
• Create data visualizations and reports using Power BI for stakeholder insights.
• Optimize cloud-based data architectures and ensure reliable data processing.

Required Skills

• 6+ years of experience in data science, machine learning, and data engineering roles.
• Proficiency in Python, PySpark, and SQL for data manipulation and analysis.
• Hands-on experience with AWS Services and Azure Databricks.
• Knowledge of Snowflake for data warehousing and management.
• Experience implementing MLOps pipelines and deploying Machine Learning models.
• Familiarity with Generative AI technologies and their integration into data systems.
• Ability to generate reports and dashboards using Power BI.

Preferred Skills

• Experience with ETL tools such as Datastage, IICS, or Abinitio.
• Knowledge of cloud platforms including GCP Bigquery, Azure Data Factory, or AWS DevOps.
• Familiarity with Tableau or Spark ecosystem enhancements.

Key Skills

Education

Any Graduate