A Data Engineer is responsible for the design and implementation of data pipelines,

drawing on a range of Hadoop technologies to support data ingest and transformation

workflows with varying complexity, requirements, and SLAs.

• Must be able to leverage both architectural as well as software development skills.


• A Data Engineer will build on and develop fluency in Big Data ingest and transformation
  
  as well as being responsible for data quality and integrity for the pipelines.


• It is also expected that a Data Engineer will contribute and collaborate with the
  
  entire stack--from Data Stewards, to Data Scientists, Machine Learning workflow &
  
  Application Developers.


• Data Engineers will work closely with other team members
  
  on system configuration, tools identification and with Data Scientists on applications and algorithms.


• Data Engineers are expected to deliver clean and scalable data profiles/open data models
  
  to facilitate reusability and flexibility for changes over time - in an agile development environment.


• Data profiles/open data models will inform the daily actions of user groups across the Organization.

A successful candidate will contribute both to the management of the organization's internal data asset and to methodologies and tools for use by users / application developers.

• At least 5-10 years experiences coding in SQL, scripting languages, Java.


• At least 3-5 years experiences with ETL, Business Intelligence, and Data Processing


• Excellent written and spoken English and French


• Experience optimizing data storage in HDFS/Parquet/Avro, Kudu, and S3 (AWS) / ADLS (Azure) Linux expertise


• Ability to code in Python / Java.


• Fundamental understanding of data storage.


• Understanding of basic principles of data governance.


• Excellent teaming and communication skills required


• Experience or fundamental understanding of PySpark and Scala a plus


• Experience with Hadoop Technologies, specifically Impala / Hive, and Spark.


• Proven ability to architect and implement high-throughput data pipelines


• Hands-on experience with Hadoop, ingest tools such as Kafka and Spark


• Experience generalizing high-throughput Hadoop workflows (e.g. Spark)


• Experience in Health would be a plus.


• Proven ability to architect and implement high-throughput data pipelines


• Ability to establish an environment of cooperation and collaboration.


• Self-motivated, with skills to support and counsel others.


• Capacity for rigor and precision, transparency and honesty.


• Results-oriented and problem-solving skills.


• Able to learn from difficult experiences, capitalize on mistakes and seize opportunities.


• Ability to communicate with non-technical staff for establishing business requirements and converting these requirements into technical specifications.


• Flexibility, availability and adaptability with possible travels to Burkina Faso


• Knowledge and experience of working with or in large international organisations; experience in INGOs or in social entreprise would be an added advantage.


• Experience in contributing to projects with team members located in several countries.


• Excellent oral and written communication skills.