Junior Analytics Engineer at Jobtailor – Johannesburg | Jobyssey

Build silver and gold data models in SQL with Lakeflow Declarative Pipelines under review.
Add expectations and data quality checks to assigned models.
Support reconciliation of Databricks outputs against SAP BW extracts during migration.
Ship changes through Git pull requests and the chapter's CI/CD.
Learn the data estate, modelling standards and SAP source context through reviews and pairing.

Requirements

Bachelor's degree in Data Science, Statistics, Computer Science, Information Systems, Engineering or a related field, or equivalent practical experience.
1 to 3 years in data or analytics work, including internships and projects.
Strong SQL fundamentals: joins, aggregations and window functions.
Understanding of dimensional modelling concepts: facts, dimensions and star schemas.
Git basics: branch, commit, pull request. The Databricks Git UI counts.
Exposure to Databricks or another cloud data platform.
Exposure to a declarative transformation framework: Lakeflow Declarative Pipelines or dbt.
Python, for the pipeline edges SQL cannot express.
Exposure to AI-assisted development with coding agents: Claude Code, Codex or similar.
Retail data, ideally pharmacy retail. Healthcare or financial services also count.
Knowledge of how retail business processes turn into facts, dimensions and metrics; learning the SAP-to-Databricks estate.
Ability to find the root cause of data problems and fix them once, in the model.
Ability to explain trade-offs to technical and business audiences.
Ability to deliver well-scoped tasks with guidance and ask early when blocked.
Ability to manage own task list; no people or workstream management.

Core Competencies

Proficient in SQL for data modeling and quality assurance, with experience in Git for version control and collaboration. Familiarity with Databricks and declarative transformation frameworks enhances the ability to support data migration and reconciliation processes.

Highest-signal resume keywords

SQL Fundamentals
Dimensional Modelling
Git Basics
Databricks Exposure
Python Programming

ATS Optimization Keywords

Hard Skills

SQL
Dimensional Modelling
Data Quality Checks
Data Reconciliation
Python
Lakeflow Declarative Pipelines
Git
Aggregations
Window Functions
Facts and Dimensions

Soft Skills

Problem Solving
Communication
Task Management
Collaboration
Adaptability

Industry Keywords

Retail Data
Pharmacy Retail
Healthcare
Financial Services
SAP

Tools & Technologies

Databricks
Lakeflow
Git
Claude Code
Codex

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