Getinz
Senior Data Engineer – GCT – Chennai
Job Description
About the Role:
We are looking for a highly skilled and motivated Senior Data Engineer to join our clients team. You will play a key role in designing, implementing, and optimizing data architectures and pipelines to support scalable data solutions for our business.
Qualifications:
- 5-8 years of experience in data engineering, with a focus on building and managing data pipelines.
- Strong proficiency in relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).
- Experience in building data pipelines with data warehouses like Snowflake, Redshift
- Experience in processing unstructured data stored from S3 using Athena, Glue etc.
- Hands-on experience with Kafka for real-time data streaming and messaging.
- Solid understanding of ETL processes, data integration, and data pipeline optimization.
- Proficiency in programming languages like Python, Java, or Scala for data processing.
- Experience with Apache Spark for big data processing and analytics is an advantage
- Familiarity with cloud platforms like AWS, GCP, or Azure for data infrastructure is a plus.
- Excellent problem-solving skills and attention to detail.
- Strong communication and collaboration skills, with the ability to work effectively in a team environment.
Key Responsibilities:
- Design, build, and maintain efficient and scalable data pipelines to support data integration and transformation across various sources.
- Work with relational databases (e.g., MySQL, PostgreSQL, etc.) and NoSQL databases (e.g., MongoDB, Cassandra, etc.) to manage and optimize large datasets.
- Utilize Apache Spark for distributed data processing and real-time analytics.
- Implement and manage Kafka for data streaming and real-time data integration between systems.Collaborate with cross-functional teams to gather and translate business requirements into technical solutions.
- Monitor and optimize the performance of data pipelines and architectures, ensuring high availability and reliability.
- Ensure data quality, consistency, and integrity across all systems.
- Stay up-to-date with the latest trends and best practices in data engineering and big data technologies.
