About Interswitch

Interswitch is an Africa-focused integrated digital payments and commerce company that facilitates the electronic circulation of money as well as the exchange of value between individuals and organizations on a timely and consistent basis. Our vision is to build an Africa where payment is a seamless part of everyday life.

Job Summary

To build reliable data integration solutions, clean, transform, and analyze vast amounts of big data from various systems using Spark and other ETL tools to provide ready-to-use datasets to data scientists and data analysts, while ensuring data quality and integrity. Collaborate with stakeholders to design scalable and efficient data solutions that enable informed decision-making, and compliance with data governance.

Responsibilities:

Data Ingestion and Extraction

• Develop and implement efficient data ingestion pipelines to acquire and extract large volumes of structured and unstructured data.
• Ensure data integrity and quality during the ingestion process.
• Integrate various data sources and formats into a unified data ecosystem.

Data Processing and Transformation

• Design and execute data processing workflows to clean, transform, and enrich raw data.
• Develop scalable data processing algorithms and techniques to handle big data volumes efficiently.
• Optimize data processing pipelines for performance and reliability.

Data Storage and Management

• Create and maintain data storage architectures that cater to the specific needs of big data applications.
• Implement robust data management strategies, including data partitioning, indexing, and compression techniques.
• Ensure data security, privacy, and compliance with relevant regulations.

Data Analysis and Modeling

• Collaborate with data scientists and analysts to understand their requirements and translate them into scalable data models.
• Apply data visualization techniques to communicate insights effectively.

Performance Optimization

• Identify and implement strategies to enhance the performance and efficiency of big data applications and systems.
• Conduct performance tuning, load testing, and capacity planning to meet scalability and throughput requirements.
• Monitor system performance and troubleshoot issues related to data processing, storage, and retrieval.

Data Governance and Compliance

• Establish and enforce data governance policies, standards, and best practices.
• Ensure compliance with data regulations, such as GDPR or HIPAA, by implementing appropriate data protection measures.
• Conduct data audits and implement data quality controls to maintain data accuracy and consistency.

Collaboration and Communication

• Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to understand their data requirements and provide technical support.
• Communicate complex technical concepts and findings to non-technical stakeholders clearly and concisely.
• Participate in knowledge-sharing activities and contribute to the continuous improvement of data engineering practices.

Documentation and Documentation

• Document data engineering processes, workflows, and system architectures for future reference and knowledge transfer.
• Prepare technical documentation, including data dictionaries, data lineage, and system specifications.
• Create and maintain documentation related to data governance, compliance, and security protocols.

Education

Academic Qualification(s):

• BSc in Computer Science/Engineering or related field.

Evidence of strong industry/sector participation and relevant professional certifications such as:

• Azure Data Engineer Associate
• Databricks Certified Data Engineer Associate
• Databricks Certified Data Engineer Professional
• Amazon Web Services (AWS) Certified Data Analytics – Specialty
• Cloudera Data Platform Generalist Certification
• Data Science Council of America (DASCA) Associate Big Data Engineer
• Data Science Council of America (DASCA) Senior Big Data Engineer
• Google Professional Data Engineer
• IBM Certified Solution Architect – Cloud Pak for Data v4.x
• IBM Certified Solution Architect – Data Warehouse V1

Experience

• At least 3 years developing, deploying, and managing robust ETL/ELT data solutions, preferably in a reputable Financial Institution or FinTech company.