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ABOUT US:
WHAT WE DO | Mondia Pay is a rapidly growing FinTech company, disrupting the payment business across 60+ countries globally, with a strong focus on Africa & emerging markets. Our talented teams create tech that connects brands to people via meaningful content that impacts their lives in positive ways.
WHY WE’RE DIFFERENT | What makes us a leader in our industry, and different from other international digital tech companies, is our ability to tailor or custom create our offering to solve business challenges.
WHERE YOU FIT IN | We aim to build an inspiring organisation with an engaged and high-performing culture. We believe in possibilities. We connect to the future. Think unlimited digital potential, global reach, limitless content, unreal experiences, real connections…now imagine the direct impact you could have in this landscape. If you are eager to work in an inspiring, dynamic environment and collaborate with like-minded people, we want to hear from you!
ABOUT THE ROLE
The purpose of our Data Engineering & Analytics Manager is to help manage existing data resources, implement new technologies and tools to further enable science and analytics, as well as help, drive scalable data sharing practices. In this role, he/she will split their time between hands-on development and managerial activities. The role will own data environments, integrate with new technologies, and oversee the development of new processes that support teams across Mondia business groups. This role will gather requirements through direct interaction with business, Technology as well as software development teams. The role will also track the performance of our resources and related capabilities, constantly evolving our offering in order to scale our capability set with the growth of the business and the needs of our customers.
Other key responsibilities include:
- Define a clear road map for the data engineering team both in terms of projects and team development, working closely with product, engineering and business.
- Develop modern techniques that will support data models and science that will enable solving business questions and unlock significant impact opportunities.
- Work closely with BI manager & ML engineers to build data infrastructure that fuels the needs of multiple teams, systems and products
- Automate manual processes, optimize data delivery and build the infrastructure required for optimal extraction, transformation and loading of data required for a wide variety of use-cases using one language or more
- Build stream processing pipelines and tools to support a vast variety of analytics, data models and real-time reporting
- Continuously evaluate relevant technologies, influence and drive architecture and design discussions
- Communicate effectively to all levels of the organization.
- Manage a team of BI managers and ensure effective performance management
ABOUT YOU
The ideal candidate will have outstanding communication skills, proven data infrastructure design and implementation capabilities, strong business acumen, and an innate drive to deliver results. He/she will be a self-starter, comfortable with ambiguity and will enjoy working in a fast-paced dynamic environment.
Other qualifications include:
- University degree in business administration or equivalent education
- 6+ years of experience in building large-scale data/software systems with high performance, scalability and availability parameters
- Good working knowledge in building Data Lakes, Data warehouses, Architecture, infrastructure components, ETL, Data Governance, Data Quality, Reporting/analytic tools and Cloud Environments
- Experience with Big Data technologies e.g. Azure, Hadoop, Hive, Sqoop and more!
- Experience with distributed systems, MySQL and NoSQL databases
- Exposure to Python, Java and Node.Js would be a plus
- Proven experience tracking analytics and exceeding sales KPIS
- Proven experience in online acquisition tactics and best practices
- Strong written and verbal communication skills
- Strong organizational skills and attention to detail
- Ability to manage multiple tasks and priorities at once
- Ability to perform well in a fast-paced, cross-functional, dynamic, and ambiguous start-up environment
