Description

You will lead data engineering efforts to enhance automation and deliver data-driven insights across the organization.

Responsibilities

• Design, build, and maintain scalable ETL/ELT processes and data pipelines across diverse database platforms.
• Architect and optimize data storage solutions to ensure reliability, security, and scalability.
• Leverage generative AI tools and models to enhance data engineering workflows and drive automation.
• Collaborate with Data Scientists, Analysts, and Engineers to deliver on specific data requirements.
• Develop and enforce data quality standards, governance policies, and monitoring systems.
• Implement data modeling best practices and optimize data retrieval processes.

Required Skills

• 5–8 years of experience in data engineering and managing large-scale data systems.
• Proficiency in Python, PySpark, and Pandas.
• Strong experience with SQL and ETL/ELT processes.
• Hands-on experience with BigQuery and Azure.
• Experience with NoSQL databases including MongoDB, Cassandra, and CosmosDB.
• Proven track record in data modeling and pipeline orchestration.
• Experience applying generative AI technologies to data workflows.
• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

Key Skills

Education

Bachelor's or Master's degrees