Fresh Jobs at Interswitch

Job Summary

• To conduct all levels of testing on new enterprise software and enhancements as per the test plan to ensure the deployment of quality solutions

Responsibilities:

• Set up the test bed, ensuring that the data used is realistic to facilitate a wholistic testing experience
• Code scripts as required for automated testing to enable the rigorous and efficient testing of software
• Carry out and coordinate all levels of testing to ensure that the developed software meets specifications and quality requirements
• Adhere to the testing plan and where there are hindrances, escalate to the
• Lead to ensure that the on-time delivery as per the project plan is not compromised
• Analyse the test results, identify bugs and other errors and provide reports to the relevant stakeholders to enable the deployment of fully functional software
• Identify shortcomings in existing processes, systems and procedures, and use established change management programs to address them

Required Qualifications

General Education

• First Degree in Computer Science or related field

Experience

General Experience

• 3 - 5 years of experience in software engineering

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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.

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Job Summary:

• At Interswitch, design is more than aesthetics — it’s a strategic engine driving innovation, growth, and impact across Africa. As the Head of Product Research, you will lead the charge in embedding insight-driven decision-making into the heart of our product, marketing, and design practices.
• This role blends UX research, product analytics, customer insights, and strategic influence to shape how we build and evolve our digital products and experiences. You will own the research vision, build a world-class research practice, and ensure our teams are equipped with the evidence they need to make bold, customer-centered decisions.

Responsibilities:

Research Strategy & Leadership

• Define and evolve the research vision, roadmap, and operating model across product and marketing.
• Build and lead a high-performing team of researchers and analysts across qualitative, quantitative, and analytics domains.
• Promote a culture of continuous discovery, experimentation, and insight-led product development.
• Champion the strategic value of research across the organization.

Insight Generation & Execution

• Oversee the design and execution of UX research, usability testing, market studies, segmentation, and behavioral analysis.
• Collaborate with product managers, designers, marketers, and data teams to identify the highest-impact research questions.
• Ensure the right methods (interviews, surveys, field studies, A/B tests, analytics, etc.) are used at the right time.
• Advance the use of AI, automation, and experimentation platforms to scale learning.

Product Analytics & Data Integration

• Utilize product analytic best practices to generate, synthesize and turn behavioral data into product and UX insights.
• Develop standard metrics and dashboards to measure product experience and inform design decisions.
• Enable a seamless loop between quantitative analytics and qualitative insight.

Communication & Influence

• Translate complex research findings into compelling, actionable insights for stakeholders at all levels.
• Deliver high-impact presentations and reports that drive alignment and decision-making.
• Foster a culture of storytelling through data, ensuring research impacts product roadmaps and go-to-market strategies.

Practice & Operations

• Establish standards, playbooks, and ethical frameworks for research across the company.
• Build and manage a centralized research repository and insight hub.
• Mentor and grow the team through structured coaching, training, and hiring.
• Drive operational excellence in research planning, documentation, and impact tracking.

Requirements:

• 8+ years of experience in UX research, product research, or insights roles, including at least 3 years in a leadership position.
• Experience in product-led organizations and working closely with design, product, and marketing teams.
• Strong track record of conducting and leading both generative and evaluative research.
• Deep expertise in UX research methods, quantitative analysis, and product analytics tools (e.g., Mixpanel, Amplitude, Clarity, Hotjar, etc.)
• Proficient in leading multi-method research programs: interviews, diary studies, surveys, fieldwork, concept testing, etc.
• Excellent verbal and written communication skills — able to influence through insights.
• Familiarity with modern AI tools for research automation and synthesis is a strong plus.

Personal Attributes

• Strategic thinker with a bias for impact and outcomes.
• Confident leader who can inspire, coach, and develop a multidisciplinary team.
• Comfortable navigating ambiguity and complexity in fast-paced environments.
• Deep empathy for users and a passion for solving real-world problems through resear