Senior Data Engineer - GPM

5 - 8 years

3 - 12 Lacs

Posted:3 days ago| Platform: Foundit logo

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On-site

Job Type

Full Time

Job Description

About the Role:

Senior Data Engineer

Qualifications:

  • 5-8 years

    of experience in data engineering, with a focus on building and managing data pipelines.
  • Strong proficiency inrelational databases(e.g., MySQL, PostgreSQL) andNoSQL databases(e.g., MongoDB, Cassandra).
  • Experience in building data pipelines with data warehouses likeSnowflake,Redshift
  • Experience in processing unstructured data stored fromS3usingAthena, Glue etc.
  • Hands-on experience withKafkafor real-time data streaming and messaging.
  • Solid understanding ofETL processes, data integration, and data pipeline optimization.
  • Proficiency in programming languages likePython,Java, orScalafor data processing.
  • Experience withApache Sparkfor big data processing and analytics is an advantage
  • Familiarity with cloud platforms likeAWS,GCP, orAzurefor 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.

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