Role & responsibilities

- Design, develop, and maintain scalable data pipelines and data engineering solutions.
- Develop data ingestion, transformation, and processing workflows using cloud-based technologies.
- Work with Snowflake and Databricks to build and optimize data processing and analytical solutions.
- Develop and maintain data pipelines using AWS Glue, S3, and Lambda.
- Implement data transformation, cleansing, validation, and integration processes.
- Develop efficient SQL queries and optimize data processing and warehouse workloads.
- Work with business and technical teams to understand data requirements and translate them into technical solutions.
- Participate in solution design, development, testing, and deployment activities.
- Develop reusable components and follow established data engineering and coding standards.
- Troubleshoot data pipeline and application issues and implement appropriate fixes.
- Participate in code reviews, technical discussions, and continuous improvement initiatives.
- Support deployment and release activities across environments.
- Monitor data pipelines and proactively identify issues affecting data processing or availability.
- Provide support for production issues when required, including troubleshooting and root cause analysis.
- Maintain technical documentation and operational procedures.

Preferred candidate profile

- 3-8 years of hands-on experience in data engineering and ETL/ELT development.
- Strong understanding of data engineering concepts, ETL/ELT, and data pipelines.
- Hands-on experience with Snowflake and/or Databricks.




- Experience building data pipelines and data transformation workflows.
- Strong SQL skills.
- Good understanding of data modelling and data warehousing concepts.
- Good experience with cloud-based data platforms and data pipelines.
- Hands-on experience with one or more of the following AWS services:

- AWS Glue

- Amazon S3

- AWS Lambda
- Experience with Databricks data engineering, including:

- Data transformation and processing

- Delta Lake

- PySpark and/or Spark
- Notebook-based development
- Experience with Snowflake development, including:

- Data loading and transformation

- SQL development

- Data warehouse concepts

- Performance optimization
- Experience with any of the following preferred/optional skills will be an advantage:

- ODI (Oracle Data Integrator)

- OAC (Oracle Analytics Cloud)

- PL/SQL

- Amazon MSK / Kafka

- Datadog

- Python

- PySpark

- CI/CD and DevOps practices

- Git

- Cloud monitoring and logging

- Oracle databases
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline.
- Strong data engineering and analytical skills.
- Good understanding of cloud data platforms.
- Strong SQL and data transformation capabilities.
- Strong problem-solving and troubleshooting skills.
- Good communication and collaboration skills.
- Ability to work independently as well as part of a team.
- Robust focus on data quality and solution reliability.
- Ability to learn and work across new technologies and platforms.

📌 Data Engineer (Chennai)
🏢 CGI
📍 Chennai