As a Hadoop big data engineer, you will develop, operate and drive scalable and resilient data platform
based on Hadoop ecosystem to address the business requirements:
• Ensure industry best practices around data pipelines, metadata management, data quality, data
governance and data privacy
• Design and implement business-specific large-scale data processing pipelines
• Work with complex data structures, manipulate, cleanse data, and perform transformations to
make insights from data.
• Responsible to Ingest data from files, streams, and databases. Process the data with PySpark,
Kafka, Hive, Hive LLAP…
• Develop efficient software code for multiple use cases leveraging Spark and Big Data
Technologies for various use cases built on the platform
• Provide high operational excellence guaranteeing high availability and platform stability.

➢ Must requirements:
• Experience in Hadoop ecosystem including HDFS, MapReduce, YARN, HBase, Zookeeper, Pig,
Hive…
• Experience in building large-scale data processing (batch-processing, stream processing)
• Experience with Apache Spark preferably in PySpark
• Understanding of SLA and meeting Timelines for support activities
➢ Good to Have:
• Experience with Hadoop distributions such as Cloudera, HortonWorks, comparison and
feasibility
• Experience in Apache Kafka, Apache Beam
• Experience with Data warehouse
• Experience in ETL
• Experience in Data management:
o Data Governance
o Data Architecture
o Data Modelling
o Data Quality
o Data integration
• Experience in SQL and NoSQL Database
• Good in programming language Python, Java
• Experience with SRE, Patching & Automation: Kubernetes or Docker & Containerization
• Experience working with Big Data on Cloud environment
• Experience with Google Cloud
• Experience in Backend development using Java
• Experience in Data API
• Good to have Architecture knowledge or experience

• From the 1st day at work: 100% full of salary
• Insurance plan based on full salary + 13th salary + Performance Bonus.
• 18 paid leaves per year (including 12 annual leaves + 6 personal leaves).
• Medical Benefit for employee and family
• Working in a fast paced, flexible, and multinational working environment. Chance to travel onsite (in 49 countries).
• Internal Training (Technical & Functional & English).
• Working from Mondays to Fridays.