The Data Engineer is responsible for designing, developing,
and maintaining scalable data solutions that transform raw data into trusted,
accessible, and actionable information. This role focuses on building and
optimizing data pipelines, data architectures, and data platforms that support
analytics, business intelligence, machine learning, and operational reporting
requirements.

The successful candidate will work closely with Data
Scientists, Analysts, Architects, and Business Stakeholders to design and
implement modern data engineering solutions that enable data-driven
decision-making across the organization.

Responsibilities

Data Engineering & Data Management

• 
  Design, develop, and maintain scalable data pipelines and
  architectures to support business and analytical requirements.
• 
  Build and optimize databases, data warehouses, and data
  lakes for performance, reliability, and scalability.
• 
  Extract, transform, and load (ETL/ELT) data from a variety
  of structured and unstructured sources.
• 
  Develop and implement automated processes for data
  acquisition, integration, cleansing, transformation, and storage.
• 
  Define and implement data storage solutions based on
  business and technical requirements.
• 
  Create and maintain physical and logical data models to
  support enterprise data initiatives.
• 
  Support data migrations across multiple databases, servers,
  and cloud platforms.
• 
  Ensure data quality, consistency, integrity, and governance
  across all data assets.

Analytics & Machine Learning Support

• 
  Collaborate with Data Scientists and Analytics teams to
  operationalize machine learning models.
• 
  Develop data pipelines that support predictive analytics,
  artificial intelligence, and machine learning workloads.
• 
  Deploy machine learning models into production environments.
• 
  Build robust testing frameworks to validate data
  transformations and model outputs.

Data Architecture & Solutions Development

• 
  Design and implement secure, scalable, and highly available
  data platforms.
• 
  Evaluate and recommend data solutions, technologies, and
  tools to address business requirements.
• 
  Develop databases optimized for analytics, reporting, and
  advanced data processing.
• 
  Build and manage cloud-based data solutions utilizing modern
  cloud technologies.

Quality Assurance & Change Management

• 
  Perform root-cause analysis and troubleshooting for
  data-related issues.
• 
  Design and execute testing scenarios to validate data
  quality and transformation accuracy.
• 
  Assess, document, and implement changes in accordance with
  change management processes.
• 
  Ensure release processes, procedures, and documentation are
  maintained and updated.
• 
  Support configuration management and release management
  activities.

Stakeholder Engagement

• 
  Collaborate with business, analytics, and technical teams to
  improve data accessibility and usability.
• 
  Translate business requirements into technical data
  solutions.
• 
  Provide recommendations regarding data architecture,
  integration, and optimization strategies.
• 
  Communicate complex technical concepts effectively to both
  technical and non-technical stakeholders.

Skills

• 
  Strong programming skills in Python, Bash, Shell Scripting, Perl
• 
  Advanced SQL development skills, including: SQL Server, MySQL
• 
  Relational database technologies: ETL/ELT processes, Data
  pipelines, Data warehouses, Data lakes
• 
  Experience working with large-scale structured and
  unstructured datasets.
• 
  Knowledge of data governance, data quality, and metadata
  management practices.
• 
  Experience building and maintaining highly available and
  scalable systems.
• 
  Understanding of cloud platforms such as: Microsoft Azure Amazon
  Web Services (AWS), Google Cloud Platform (GCP), Hadoop, Cassandra, Storm, Similar
  distributed processing frameworks

Analytics & Reporting

• 
  Working knowledge of
  Power BI
  for
  dashboards, reports, and analytical solutions.
• 
  Understanding of Data visualization, Data virtualization, Augmented
  analytics, Business intelligence solutions.

Requirements

• 
  8+ years Proven experience in a Data Engineering role within
  a fast-paced technology environment.
• 
  Matric and a Bachelor's Degree in Computer Science,
  Information Technology
• 
  Certified Data Engineer certification.
• 
  Cloud certifications (Azure, AWS, Google Cloud).
• 
  Professional data and analytics certifications.
• 
  Experience developing modern data and analytics platforms
  that deliver actionable insights from large and complex datasets.
• 
  Strong hands-on experience with Python development.
• 
  Experience designing and supporting ETL/ELT frameworks and
  data integration solutions.
• 
  Experience working with SQL Server, MySQL, and enterprise
  database solutions.
• 
  Experience with cloud technologies, including SaaS, PaaS,
  and IaaS environments.
• 
  Experience with automation, scripting, and data process
  orchestration.
• 
  Experience building secure, scalable, resilient, and highly
  available data platforms.
• 
  Experience supporting machine learning and advanced
  analytics initiatives.
• 
  Experience with big data technologies and distributed
  computing environments.