NTT DATA Data Engineering Job Alerts | Bengaluru

Qualifications

Required Skills:

• Strong ETL developers with Java & Flink experience
• ETL tool :Informatica
• Proficiency in programming languages such as Python,  or Scala.
• Experience with data processing frameworks such as  Flink.
• Strong knowledge of SQL and experience with relational databases (e.g., PostgreSQL, MySQL).
• Familiarity with NoSQL databases (e.g., MongoDB, Cassandra).
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Understanding of data warehousing concepts and tools (e.g., Databricks, Snowflake).
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.
• Ability to work in a fast-paced, dynamic environment.

Preferred Qualifications:

• Bachelor’s degree in computer science, Engineering, or a related field.
• Experience with data orchestration tools.
• Knowledge of data modeling and schema design.
• Familiarity with containerization and orchestration tools like Docker and Kubernetes.
• Experience with real-time data processing and streaming technologies.

Job Description:

Seeking a talented Data Engineer to join our team. The ideal candidate will have a strong background in data engineering, with experience in designing, building, and maintaining scalable data pipelines and infrastructure.

You will work closely with data scientists, analysts, and other stakeholders to ensure that data is accessible, reliable, and ready for analysis.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL processes.
• Work with large datasets to extract, transform, and load data from various sources.
• Implement data integration solutions to consolidate data from multiple systems.
• Optimize and tune data pipelines for performance and reliability.
• Collaborate with data scientists and analysts to understand data requirements and deliver solutions.
• Ensure data quality and integrity through rigorous testing and validation.
• Develop and maintain data infrastructure, including databases, data warehouses, and data lakes.
• Monitor and troubleshoot data pipeline issues and implement solutions.
• Stay up-to-date with the latest industry trends and technologies in data engineering.