Head of Data Engineering at AES Africa

Role Purpose:

This is an incredible opportunity to work at the forefront of the industry, with incredible minds and leading talent. Working as a core member of an Agile team, you will hold responsibility for building and supporting data pipelines. You must be experienced in handling raw data, from a broad range of sources and integrate them seamlessly. You will enable solutions, using emerging technologies across the big data and cloud spaces.

Tools:

• Talend
• AWS: EMR, EC2, S3
• Python
• PySpark or Spark
• Business Intelligence Data modelling
• SQL

Key responsibilities:

• Responsible for data solution software and hardware required.
• Strategic thinker, understanding the commercial requirements and translates them into system requirements.
• You must have experience of building DA frameworks; you will architect next-generation analytics framework. This will be developed on the Group’s range of core technology.
• Build a strong working relationship with developers, you will be responsible for making sure data solutions are integrated.
• You will Build automation tools, ensuring that all automated processes preserve integrated data.
• You will liaise with key stakeholders across the business, Interpreting data results for business customers.
• You will work with the business to maintain a fully adaptable technical solution.
• This role is responsible for communication across third parties and product managers (tech/non-tech) on solution design.

Candidate Requirements:

• Bachelor's in computer science, computer engineering
• AWS Certification – this must be from Associate +
• Data engineering or software engineering experience 5+ yrs
• Experience of leading a team of engineers 3+ yrs
• Big Data, ETL, Could AWS
• Agile or similar/ Scrum
• Experienced coding and testing pattern
• Creating data channels from on-site to AWS Cloud 2 + yrs
• Talend or similar
• Data manipulation using python and pyspark
• Hadoop paradigm for processing data
• Experienced in devops across Big Data and BI, including automated testing and deployment