Description

Responsibilities:

• Design, develop, and maintain robust data pipelines to support AI/ML applications.
• Collaborate with data scientists to understand data requirements and ensure data quality.
• Implement data models and algorithms that enhance data processing and analysis.
• Optimize data storage and retrieval processes for performance and scalability.
• Monitor and troubleshoot data pipeline performance and reliability.
• Document data architecture and processes for future reference and compliance.
• Stay updated with the latest trends in AI/ML technologies and best practices.

Mandatory Skills:

• 7 10 years of experience in data engineering or related fields.
• Strong knowledge of AI, ML, and DL concepts and frameworks.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with data processing frameworks like Apache Spark or Hadoop.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their data services.
• Solid understanding of SQL and NoSQL databases.
• Experience with data warehousing solutions and ETL processes.

Preferred Skills:

• Experience with containerization technologies (Docker, Kubernetes).
• Knowledge of data visualization tools (Tableau, Power BI).
• Familiarity with big data technologies (Kafka, Flink).
• Experience in deploying machine learning models into production.
• Strong problem solving skills and ability to work in a fast paced environment.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Proven track record of successful data engineering projects.
• Excellent communication and collaboration skills.
• Ability to work independently and as part of a team

Key Skills

Education

Bachelor's or Master's degrees