Description

Key Skills: SCALA, Pyspark, Spark, Python, AWS

Roles and Responsibilities:

• Develop and maintain reliable data pipelines to ingest, transform, and move data from multiple sources into data lakes or data warehouses
• Build ETL/ELT workflows to extract, transform, and load data ensuring clean and structured outputs
• Design, build, and optimize relational and NoSQL databases for performance and scalability
• Implement data validation checks, monitoring, and error handling to ensure data accuracy and consistency
• Optimize data processing workflows for performance, scalability, and efficiency
• Implement data architecture and security practices including encryption, access control, and efficient data structures
• Collaborate with stakeholders to understand data requirements and translate them into engineering solutions

Skills Required:

• 3-6 years of experience in data engineering or related roles
• Strong hands-on experience with Scala, Spark, and PySpark
• Proficiency in Python for data processing and pipeline development
• Experience in building and maintaining ETL/ELT pipelines
• Understanding of data lake and data warehouse architectures
• Knowledge of relational and NoSQL database systems
• Experience with data validation, monitoring, and error handling techniques
• Strong understanding of data security practices (encryption, access control)
• Exposure to AWS cloud platform (preferred)
• Strong analytical and problem-solving skills

Education: B.Tech / Dual Degree (B.Tech + M.Tech) in Computer Science or Computer Science - Bioinformatics

Key Skills

Education

Any Graduate