Analytics Engineer: Data Products & Lakehouse Architect

Uberall; South Africa; On-site; ZAR 900,000 - 1,500,000; Full time

Job summary

Uberall is seeking an Analytics Engineer to turn raw product, commercial, and vendor data into trusted data products used across the business. You will own the transformation layer of the Databricks lakehouse, from curated models to datasets and dashboards, ensuring reliability, documentation, and performance.

The role blends analytical rigor with practical data delivery, designing data products that are easy to read and act upon by stakeholders.

Qualifications

• Experience with dimensional modeling for analytics warehouses is required.

Responsibilities

• Design and build dbt models that turn raw sources into curated data.
• Apply dimensional modeling to shape facts and dimensions for analytics.
• Model transactional sources originating from CDC and 3NF patterns.
• Define and enforce naming conventions and project structure.
• Build and maintain data products and datasets for internal stakeholders.
• Deliver clear, well-designed reporting in Metabase and Pigment.
• Translate business questions into data models with stakeholders.
• Enable safe, governed data sharing across teams.
• Own the health of production pipelines orchestrated in Databricks or Apache Airflow.
• Set up monitoring, alerting, and data quality checks.
• Manage CI/CD pipelines, schema migrations, and safe releases.
• Tune performance and cost of workloads on columnar engines.
• Establish reusable development patterns and code review standards.
• Maintain model documentation, lineage, and column-level metadata.
• Contribute to governance standards and data contracts with stakeholders and source teams.
• Support vendor and third-party data ingestion as a secondary focus.

Skills

Dimensional modeling

dbt

SQL

Python

Git

Databricks

Apache Airflow

AWS

Metabase

Pigment

Tools

dbt

Databricks

Apache Airflow

Metabase

Pigment

Delta Lake

AWS

Job description

Uberall is seeking an Analytics Engineer to turn raw product, commercial, and vendor data into trusted data products used across the business. You will own the transformation layer of the Databricks lakehouse, from curated models to datasets and dashboards, ensuring reliability, documentation, and performance.

The role blends analytical rigor with practical data delivery, designing data products that are easy to read and act upon by stakeholders.