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Job Description / Job Responsibilities:

• Build distributed, scalable, and reliable data pipelines that ingest and process　data at scale and in real-time.
• Collaborate with other teams to design and develop and deploy data tools that support both operations and product use cases.
• Perform offline analysis of large data sets using components from the Hadoop ecosystem.
• Evaluate and advise on technical aspects of open work requests in the product backlog with the project lead.
• Own product features from the development phase through to production deployment.
• Evaluate big data technologies and prototype solutions to improve our data processing architecture.

Candidate Profile:

• BS in Computer Science or related area
• Around 6 years software development experience
• Minimum 2 Year Experience on Big Data Platform
• Must have active current experience with Scala, Java, Python, Oracle, HBase, Hive
• Flair for data, schema, data model, how to bring efficiency in big data related life cycle
• Understanding of automated QA needs related to Big data
• Understanding of various Visualization platform
• Experience in Cloud providers like AWS preferable
• Proficiency with agile or lean development practices
• Strong object-oriented design and analysis skills
• Excellent written and verbal communication skills
• APIGEE

Qualifications

Top skill sets / technologies in the ideal candidate:
* Programming language -- Java (must), Python, Scala

Database/Search – Oracle, complex SQL queries, stored procedures, performance tuning concepts, SOLR, AWS RDS,  AWS Aurora

Batch processing -- Hadoop MapReduce, Cascading/Scalding, Apache Spark, AWS EMR
Stream processing -- Spark streaming, Kafka, Apache Storm, Flink
NoSQL -- HBase, Cassandra, MongoDB.