Description

You will own the design, development, and deployment of scalable distributed data processing and replication strategies. You will integrate new data sources into the big data ecosystem and mentor onsite and offshore developers on architectural guidance.

Responsibilities

• Design and implement scalable data ingestion and transformation pipelines using Java, Spark, Python, and Scala.
• Analyze complex systems and collaborate on data-driven product designs from development through production deployment.
• Perform large-scale data analysis using Hadoop ecosystem components including HDFS, HBase, and Hive.
• Evaluate emerging technologies and prototype solutions to enhance data processing architecture.
• Ensure adherence to secure application development standards and automated QA practices.

Required Skills

• 5+ years of experience delivering enterprise software solutions with significant big data exposure.
• Strong hands-on expertise in Java, Apache Spark, Scala, and Python for distributed applications.
• 3+ years working with Hadoop and Spark ecosystem technologies (MapReduce, HDFS, HBase, Hive, Flume, Sqoop, Kafka).
• Proven experience with AWS Cloud technologies and implementing scalable cloud solutions.
• Deep understanding of data modelling, schema design, and optimization techniques.
• Experience with object-oriented design, Agile development, and automated QA processes.
• Bachelor’s degree in Computer Science, Computer Engineering, or equivalent.

Preferred Skills

• Hands-on experience with Apache Airflow and Python-based workflow orchestration.
• Ability to translate business requirements into effective technical implementations quickly.

Key Skills

Education

Any Graduate