Big Data Engineer
- Our customer is looking for a big data engineer with experience in big data ecosystem to work in a customer facing capacity.
- As a big data engineer you will interact with various stakeholders business, solution designer, data scientists and enterprise architect.
- You will be able to understand their requirements and develop and create an evolving solution for data lake platform. There is a real emphasis on professional delivery as you will be working closely with stakeholders providing excellent delivery of service.
- Whilst working for a forward thinking company you are expected to have a real desire to learn and adapt to new technologies to be a force for change within the bank.
The DBIG Team (Big Data and Analytics) is responsible within the company's IT unit to develop and maintain the applications that deliver commercial information to the bank and mainly to Retail Banking and Public-Corporate divisions.
The team covers mainly next domains:
- The support of the campaign activity and the feeding of the new operational Analytics Based Selling system (Lily).
- Follow-up and monitoring of customer's channels through tagging solution (Adobe)
- The setup of a big data environment in support of the data scientists and a data lake to automate data science models execution.
Some key technologies/environment you can look forward to working with:
- Hadoop ecosystem e.g. Cloudera, Apache Spark, Kerberos
- NoSQL technologies e.g. HBase
- Streaming technologies : Kafka, flume, hoozie
- Change data Capture toolings
- Oracle big data appliance
- Data science language & tools: R, python, Jupyter, Bitbucket
- Big Data (Hadoop, Hbase, ...)- Medior, 5 years of experience
- Deep understanding of Big Data technologies e.g. Cloudera, YARN, Spark, Hive, Impala, Sqoop, Kafka, Kerberos, etc.
- Able to develop in python, pyspark, sparksql and R.
- Hands on experience of working in Linux and Data Lake environment
- Able to work in agile mode and on large scale and complex projects for the banking industry