ETL code review
Line-by-line review of transformation logic, incremental load patterns, and error handling, delivered as a prioritised findings memo your team can ticket immediately.
East London · Remote-friendly
Your ETL jobs deserve a second pair of eyes before they touch production
Terra Pipeline is a programming consultancy focused on data pipeline development and written ETL code reviews. We read your SQL, Python, and orchestration configs the way an on-call engineer would — flagging load risks, test gaps, and naming drift before the nightly batch fails.
Consulting built around pipelines, not slide decks
Whether you are wiring a new warehouse feed or untangling a legacy stored-procedure chain, we stay inside the repository: diffs, job logs, and dependency graphs — not abstract roadmaps.
Pipeline design sessions
Half-day working sessions to map sources, grain, and refresh windows before you commit to a scheduler layout or folder structure.
Handover & runbook audit
We compare what your README promises against what the jobs actually do — catching silent full refreshes and missing rollback notes.
Recent review: retail stock reconciliation feed
A Gauteng retailer asked us to review a dbt project that merged store-level POS extracts with a central inventory table. We found duplicate surrogate keys on partial loads and suggested a single merge predicate — their team merged the fix in one sprint.
Read more client stories“The review called out our timezone assumption on close-of-business rows — something three internal passes had missed. The write-up was blunt in places, which we needed.”
— Lindiwe M., data engineer, FMCG
From the field notes
Practical notes on batch jobs, review scope, and pipeline boundaries — written for engineers maintaining nightly loads.
What we check first on a batch ETL review
Grain, late-arriving facts, and idempotency keys — the opening pass before we open style debates.
Choosing slice boundaries when a pipeline grows past one repo
How teams split orchestration without losing observability on shared dimensions.