Senior Data Engineer

1 week ago

Chennai, Tamil Nadu, India Weekday AI Full time ₹ 20,00,000 - ₹ 25,00,000 per year

This role is for one of Weekday's clients
Min Experience: 6 years
Location: Chennai
JobType: full-time

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: 

  • 6-9 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.

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