Intermediate Analytics Engineer

About the role

Our client, a fast-growing data and technology business, is looking for an Intermediate Analytics Engineer to build the data layers the business runs on.

You’ll create the silver and gold layers on Databricks: canonical models and certified metrics in SQL, backed by tests and documentation that keep them trustworthy. Dashboards, analysts, applications and AI agents will all use the same certified tables and metric views, so every measure is defined once and used everywhere.

The team is migrating from SAP BW to Databricks, so you’ll work with SAP data every day and help make sure migrated reports can be trusted.

What you’ll do

• Build silver and gold models. Design models in Databricks using Lakeflow Declarative Pipelines and dimensional modelling, giving the business one consistent, fast layer to query. Keep all business rules, joins and aggregations inside the models rather than in downstream tools.

• Define certified metrics. Agree metric definitions with their owners and publish them in gold tables and Unity Catalog metric views, so every consumer, human or AI agent, gets the same number. Maintain one authoritative definition per metric, with owner, grain, lineage and metadata.

• Own quality and migration assurance. Add expectations and data quality checks to every model so issues are caught before anyone sees them. Reconcile Databricks outputs against SAP BW extracts during the migration.

• Ship safely and govern well. Deliver changes through Git pull requests, GitHub Actions and Databricks Asset Bundles, so every change is reviewed, tested and reversible. Apply access control, masking and row filters in line with data sensitivity.

What you’ll bring

• Bachelor’s degree in Data Science, Statistics, Computer Science, Information Systems, Engineering or a related field, or equivalent practical experience

• 3+ years in analytics engineering, data engineering or advanced analytics

• Expert SQL: window functions, CTEs, complex joins and large analytical models, plus the judgement to write queries that stay correct and performant on full historical data

• Strong data modelling: star schemas, dimensional modelling, fact and dimension design

• Experience with a declarative transformation framework such as Databricks Lakeflow Declarative Pipelines or dbt. A Databricks Certified Data Engineer Associate or dbt Analytics Engineering certification also counts

• Git and CI/CD in data work: pull requests, code review and automated deployment

• Working SAP knowledge: BW objects such as InfoProviders, extractors and routines, plus S/4HANA or Business Data Cloud

Nice to have

• Experience with retail data. Healthcare or financial services also count

• Working Python for pipeline unit tests and transformations SQL can’t express

• Experience with coding agents such as Claude Code or Codex, including reconciling ported models against their source

• Exposure to Power BI or Qlik and how BI tools consume analytical models

You’ll thrive here if you

• Turn ambiguous business rules into clear, testable logic

• Find the root cause of data problems and fix them once, in the model

• Understand the cost of a wrong number and prioritise by business value

• Treat tests, documentation and reconciliation as part of “done”

• Explain trade-offs clearly to both technical and business people

• Own your models end to end and feel comfortable in a migration where priorities shift

This is an individual contributor role with no people management.

Requirements

• South African citizenship

• Successful background, criminal record and credit checks