Data engineering
Batch-to-streaming conversion
An existing nightly estate turned incremental without a rewrite, one pipeline at a time.
10–16 weeksTypical duration
The problem this solves
Your business asks for today's numbers and your platform produces yesterday's, because everything is a nightly batch.
What you receive
Artefacts you can hold, and that you can accept or refuse — never a list of activities.
- A conversion order, ranked by business value against conversion risk
- The first pipelines converted, running incrementally beside the batch versions
- An equivalence harness proving the streaming output matches the batch output
- The cutover plan, with the batch path retained until the equivalence holds
Also in data engineering
Lakehouse foundation
An open-table-format estate with the catalogue, the layout, the compaction and the retention decided rather than defaulted.
Streaming backbone
A Kafka and structured-streaming spine with exactly-once semantics, checkpointing and replay, built so a late record has a defined fate.
Data contracts & schema governance
A schema registry and an enforcement point, so a producer cannot break a consumer silently.