Junior Analytics Engineer

Jobtailor; Johannesburg; On-site; ZAR 320,000 - 520,000; Full time

Job summary

Jobtailor is seeking a data-focused professional in Johannesburg to build SQL-based data models using Lakeflow Declarative Pipelines, and to implement data quality checks. You will contribute to reconciling Databricks outputs with SAP BW extracts during migration and push changes via Git-based CI/CD workflows.

The role emphasizes learning the data estate, standards, and SAP-Databricks context through reviews and pairing, with 1–3 years of practical data analytics experience and strong SQL skills.

Qualifications

• Bachelor's degree in data-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.
• Exposure to Databricks or another cloud data platform.
• Exposure to 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.

Responsibilities

• 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.

Skills

SQL Fundamentals

Dimensional Modelling

Data Quality Checks

Data Reconciliation

Python Programming

Git Basics

Databricks Exposure

Lakeflow Declarative Pipelines

Education

Bachelor's degree in Data Science, Statistics, CS, IS, Engineering or related field

Tools

Databricks

Lakeflow

Git

Claude Code

Codex

Job description

• 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