On-Site
Full-Time
Kochi, Kerala
India
Skills
Artificial Intelligence (AI)
Python (Programming Language)
Computer Science
Data Engineering
Analytical Skills
Data Science
Extract, Transform, Load (ETL)
Apache Spark
Big Data
Data Analytics
About the Role
The Data Engineer will be responsible for designing, developing, and maintaining scalable data pipelines and infrastructure to support AI-driven applications. This role requires close collaboration with data scientists, analysts, and software engineers to ensure efficient data processing, storage, and retrieval. The ideal candidate will have expertise in data engineering, big data technologies, and cloud computing, enabling the AI team to leverage high-quality and well-structured data for advanced analytics and machine learning models.
Key Responsibilities:
· Design and implement scalable and robust data pipelines to support AI and machine learning initiatives.
· Develop and optimize ETL processes for data ingestion, transformation, and storage.
· Ensure data quality, consistency, and security across the AI data infrastructure.
· Work closely with data scientists to support feature engineering and model deployment.
· Implement and maintain data lake, data warehouse, and real-time streaming architectures.
· Collaborate with DevOps and software engineering teams to integrate data pipelines into production environments.
· Monitor, troubleshoot, and improve system performance and reliability.
· Evaluate and recommend new technologies to enhance the AI data infrastructure.
Requirements:
· Bachelor's or Master’s degree in Computer Science, Information Technology, or related field.
· Minimum of 3-5 years of experience in data engineering, big data processing, or cloud-based data solutions.
· Proficiency in programming languages such as Python, SQL.
· Hands-on experience with cloud platforms (AWS, Azure) and big data technologies (Spark, Hadoop, Kafka, etc.).
· Strong knowledge of relational and NoSQL databases (MongoDB, etc.).
· Experience with data orchestration and workflow management tools like Apache Airflow.
· Understanding of machine learning pipelines and MLOps best practices.
· Excellent problem-solving and analytical skills.
· Strong communication and collaboration abilities to work effectively in a cross-functional team.
Key Responsibilities:
· Design and implement scalable and robust data pipelines to support AI and machine learning initiatives.
· Develop and optimize ETL processes for data ingestion, transformation, and storage.
· Ensure data quality, consistency, and security across the AI data infrastructure.
· Work closely with data scientists to support feature engineering and model deployment.
· Implement and maintain data lake, data warehouse, and real-time streaming architectures.
· Collaborate with DevOps and software engineering teams to integrate data pipelines into production environments.
· Monitor, troubleshoot, and improve system performance and reliability.
· Evaluate and recommend new technologies to enhance the AI data infrastructure.
Requirements:
· Bachelor's or Master’s degree in Computer Science, Information Technology, or related field.
· Minimum of 3-5 years of experience in data engineering, big data processing, or cloud-based data solutions.
· Proficiency in programming languages such as Python, SQL.
· Hands-on experience with cloud platforms (AWS, Azure) and big data technologies (Spark, Hadoop, Kafka, etc.).
· Strong knowledge of relational and NoSQL databases (MongoDB, etc.).
· Experience with data orchestration and workflow management tools like Apache Airflow.
· Understanding of machine learning pipelines and MLOps best practices.
· Excellent problem-solving and analytical skills.
· Strong communication and collaboration abilities to work effectively in a cross-functional team.
Apply for this position
Application Status
Application Draft
In Progress
Submit Application
Pending
Review Process
Expected within 5-7 days
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