Purpose Statement
To bridge the gap between Data Engineers and Data Analysts by transforming complex data into accessible, reliable, and performant data models and insights that drive organizational decision-making.
To collaborate with stakeholders to understand analytical needs, partnering with Data Architects and Data Modelers to design scalable data models aligned with enterprise strategy.
Design and build efficient, reproducible data assets (including data models and marts, semantic layer, working environments etc), along with scalable transformations and pipelines that empower both Analytical Engineers and Data Analysts to deliver insights and reports with speed, consistency, and minimal friction.
Experience
Minimum:
Length of experience required is conditional on the qualifications obtained but must include:
Experience in data analytics or engineering roles.
Hands-on experience building data pipelines and dashboards.
And/or Internships or academic projects involving data pipelines or analytics tools.
Familiaritly with reporting tools like PowerBI
Qualifications (Minimum)
Bachelor's Degree in Analytical/Data/Technical
Qualifications (Ideal or Preferred)
Honours Degree in Analytical/Data/Technical
Knowledge
Min:
Basic understanding of:
Data modeling concepts (e.g., star/snowflake schemas).
ETL/ELT processes.
Data warehousing (e.g., BigQuery, Snowflake, Redshift).
Familiarity with version control (e.g., Git).
Skills
Attention to Detail
Communications Skills
Problem solving skills
Reporting Skills