As a Hadoop Big Data Engineer, you will operate and monitor scalable and resilient data platform based on Hadoop ecosystem to address the business requirements:

Development Tasks (30%)
– Engineer reliable data pipelines for sourcing, processing, transforming, enriching and storing data in different ways, using data platform infrastructure effectively
– Ingest and transform data sets from a variety of data sources
– Focus on ingesting, storing, processing, and analyzing large datasets
– Create scalable, high-performance web services for tracking data

Supporting Tasks (70%)
– Provide high operational excellence guaranteeing high availability and platform stability.
– Technical analysis, trouble shooting and fixing the Production Incidents, Problem tickets and Changes
– Take ownership of (Data processing/Batch Jobs) applications from a Support & Maintenance perspective
– Work on small enhancements (Analysis, Build/test, Deployment/Release support)

Must have requirements:
– Must have 3+ years of experience at a similar role
– Having hands on experience in Hadoop ecosystem (on-prem) including Spark, HDFS, MapReduce, YARN, …
– Good in programming language Python
– Experience in monitoring large-scale data processing job (batch-processing, stream processing)
– Understanding of SLA and meeting Timelines for support activities

Good to Have:
– Experience with Hadoop distributions such as Cloudera, HortonWorks, comparison and feasibility
– Experience with Data warehouse and Data management: Data Quality, Data integration
– Experience in ETL, SQL and NoSQL Database
– Experience with SRE, Patching & Automation: Kubernetes or Docker & Containerization
– Experience working with Big Data in a Cloud environment
– Experience in Backend development using Java
– Experience in Data API
– Good to have Architecture knowledge or experience