Staff Augmentation

SAP-data SaaS: client reports from hours to minutes

Backend engineer integrated into a SAP-data SaaS platform, automating client-report delivery from hours to minutes.

Industry
B2B SaaS · SAP
Stack
Node.js, RFC, OData
Status
Ongoing, month 12

Who they are

A B2B SaaS company building an intermediary platform between SAP-based enterprise systems and end-business users. Mid-size, 15–25 person team, serving customers across DACH and broader EU. Core product helps non-technical analysts extract custom reports from SAP without needing in-house SAP consultants.

What was on the table

SAP integration is notoriously hard to outsource. The platform required a specific blend of skills – Node.js for the core service layer, SAP-side knowledge for the integration logic (RFC calls, OData, field mapping), and the business-context awareness to translate vague client requests into clean data flows.

What looked like a “we need a backend dev” request was really three things at once: a Node.js senior, a SAP-savvy integrator, and someone who could think in terms of business logic for end users, not just technical specs.

The client had been burned before by senior CVs that fell apart on SAP-specific questions. They needed someone who could ship from day one, not someone who’d “learn SAP on the job.”

Why they chose UASoftDev

We had a senior backend engineer with prior SAP-integration experience in our active network – a rare profile on the UK/EU staff-aug market. CV reviewed by Alexander (CTO) before sending, vetted against the client’s specific stack requirements.

First match within 60 hours.

What the engineer delivered

  • Built the request-handling pipeline: incoming client request → SAP query construction → data extraction → JSON-formatted delivery
  • Developed data mappers translating SAP-native field structures into business-readable formats
  • Used SAP-specific extraction tools (RFC calls and OData endpoints) for targeted data retrieval, replacing the previous semi-manual workflow
  • Implemented validation and error-handling logic: invalid requests, missing SAP data, and edge cases now return clear responses instead of silent failures
  • Set up CI/CD pipeline for the integration service, eliminating manual deployment steps

What changed

The previously semi-manual SAP-report workflow was replaced with a fully automated pipeline. Business analysts on the client’s customer side now receive custom reports in minutes instead of hours, with ~60% fewer error-related support tickets.

The engagement is ongoing in its 12th month, with the developer now leading new feature work alongside the in-house team.

~40%
Reduced dependency on external SAP consultants
Enterprise customers served without scaling support team
Minutes
Report delivery time (was: hours, manual)
Solid
Foundation for future product expansion

By the numbers

60h
to first match
12 mo
ongoing
0
replacements needed
~60%
error tickets cut
~40%
less SAP consult cost

Suggested angle: Our Senior Data Engineer came in with deep data fundamentals: AWS, Redshift, Kafka, production pipelines, not an SAP specialist. SAP was new territory. He dug into the RFC/OData layer from scratch, shipped the first working integration within the first week, and never needed hand-holding on the basics. That's a great example of a strong engineering foundations transfer you don't always need a niche specialist, you need someone senior enough to figure it out fast and own it from day one.

Need a Senior Data Engineer who ships from day one?

If you're building a data platform, automating reporting pipelines, or integrating enterprise systems AWS, Azure, GCP, Redshift, Kafka, Spark, or legacy stacks like SAP, Oracle, ServiceNow and you need someone who takes ownership from day one, this is exactly what we work through Staff Augmentation.

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