CrossBoundary Access is recruiting a Data Engineer.

The Data Engineer will be responsible for accessing raw data from diverse sources, transforming it into clean, actionable datasets, and supporting the analysis of these datasets for the Access team. This individual will be setting up the data infrastructure and data processes for Access, leveraging the infrastructure already in place within CrossBoundary. They will apply software engineering best practices to design, build, and maintain data pipelines and models, working closely with business users to deliver transparent and effective data solutions. The Data Engineer will be Access’s first data hire and will report to the Commercial Director.

Who You Are

• Self-starter who is passionate about creating lasting change in Africa
• Pioneer who is excited to work with new technologies and innovations
• Creative thinker with an ability to craft non-traditional and innovative solutions to practical problems
• Can build strong relationships with clients and colleagues in stressful environments
• Empathetic and thoughtful leader that can drive performance within a multi-disciplinary team
• Comfortable with ambiguity; ability to operate effectively in a changing, challenging context

Primary Responsibilities

• Design and implement data extraction, transformation, and loading processes
• Build and manage a centralized data repository to support business intelligence and machine learning applications
• Utilize tools such as SQL, Python, and cloud-based data infrastructure platforms (AWS Redshift, Azure, Google Cloud) to maintain data pipelines
• Apply data modeling principles to prepare datasets for analysis
• Collaborate with the business users to deliver transparent and effective data analyses and solutions
• Ensure high performance, availability, and quality of data systems through monitoring and optimization
• Collaborate on data governance policies to ensure data compliance and security
• Document and communicate data architecture and processes to Access leadership

Qualifications

Required skills and qualifications:

• Bachelor's degree or equivalent professional certification in computer science, data, or related field
• 2-4+ years’ experience working in data engineering
• Highly skilled in building and maintaining ELT processes for a range of complex data sources, including open-source APIs
• Confident in designing and implementing industry-standard data modelling principles to prepare datasets for analysis
• Experience working with data lake and/or Lakehouse data architectures
• Highly skilled in SQL
• Skilled in data warehousing – Kimball technology
• Proficient at working with cloud-based data tools; preference for experience with Snowflake, dbt, and Azure Data Factory
• Experience applying software engineering best practices and guidelines to analytics code and data model development
• Strong interest in Microsoft stack technologies
• Passion for learning new technologies and tools
• Extremely curious and flexible
• Strong presentation skills, ability to communicate clearly and effectively across diverse audiences

The ideal candidate will also have the following skills and qualifications:

• Python
• dbt
• Snowflake
• Azure Data Factory
• Microsoft Azure
• Microsoft Dynamics
• Ability to build strong relationships with partners and colleagues in challenging environments
• Comfort with ambiguity and an ability to operate effectively in a changing context
• French speaking

• Design and implement data extraction, transformation, and loading processes
• Build and manage a centralized data repository to support business intelligence and machine learning applications
• Utilize tools such as SQL, Python, and cloud-based data infrastructure platforms (AWS Redshift, Azure, Google Cloud) to maintain data pipelines
• Apply data modeling principles to prepare datasets for analysis
• Collaborate with the business users to deliver transparent and effective data analyses and solutions
• Ensure high performance, availability, and quality of data systems through monitoring and optimization
• Collaborate on data governance policies to ensure data compliance and security
• Document and communicate data architecture and processes to Access leadership

• SQL
• Python
• dbt
• Snowflake
• Azure Data Factory
• Microsoft Azure
• Microsoft Dynamics
• Data modeling
• Data warehousing (Kimball technology)
• ELT processes
• Data lake and/or Lakehouse data architectures
• Software engineering best practices
• Presentation skills

• Bachelor's degree or equivalent professional certification in computer science, data, or related field
• 2-4+ years’ experience working in data engineering
• Highly skilled in building and maintaining ELT processes for a range of complex data sources, including open-source APIs
• Confident in designing and implementing industry-standard data modelling principles to prepare datasets for analysis
• Experience working with data lake and/or Lakehouse data architectures
• Highly skilled in SQL
• Skilled in data warehousing – Kimball technology
• Proficient at working with cloud-based data tools; preference for experience with Snowflake, dbt, and Azure Data Factory
• Experience applying software engineering best practices and guidelines to analytics code and data model development
• Strong interest in Microsoft stack technologies
• Passion for learning new technologies and tools
• Extremely curious and flexible
• Strong presentation skills, ability to communicate clearly and effectively across diverse audiences
• Ability to build strong relationships with partners and colleagues in challenging environments
• Comfort with ambiguity and an ability to operate effectively in a changing context
• French speaking