Senior Data Engineer

Location
Malta
Salary
Competitive
Contact
Lourens Pahud de Mortanges
Job Ref
776369
  • Great location
  • Exceptional benefits like free parking
  • Awesome company
Reporting to the Data Engineering Manager, the successful candidate will be responsible for developing and optimising the Bank's data flow and collection. The selected candidate will collaborate with stakeholders at all levels, including Business, Operations, and Technology team members, and will have a high interest in keeping up with latest industry best practices.

Duties and responsibilities
  • Designing, developing, testing and supporting data collection and data integration with batched ETL and Real-time data processing
  • Using analytical and statistical approach in building of data sets and driving business
  • decisions
  • Writing scalable code for managing Batch and Real-time data processing, making use of onsite/cloud tools and storage
  • Improving existing batch based ETLs, possibly integrating them in real-time data transformations
  • Assisting in maintaining the existing infrastructure and its migration
  • Maintaining records and documentation as evolutions/revisions occur
  • Building analytical tools that utilise the data pipeline, to provide actionable insights into key customer business performance metrics
Required knowledge, skills and experience
  • Experience in designing and implementing data streaming solutions involving but not limited to technologies such as Kafka, NiFi and Spark Streaming
  • Strong analytical and troubleshooting skills working in a Linux environment
  • Experience with Linux based scripting tools such as shell and bash, and programming languages like Java and Python
  • Good knowledge of cloud technologies and their tools for assisting in the data transformation
  • Good knowledge of PostgreSQL streaming replication and RHEL based Linux for support

Requirements
  • Excellent written and verbal communication skills in English
Being familiar with:
  • Data architecture and SQL querying on Oracle, MS SQL, PostgreSQL and HIVE
  • Using data pipeline tools such as Talend and Nifi
  • Data structures such as JSON, XML and CSV
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