Solution Architect

Beroe Inc; India; Presencial; INR 3.000.000 - 7.000.000; Tempo integral

Resumo da vaga

Beroe Inc. is seeking a Solutions Architect for MAX to act as the technical bridge between customer IT/data teams and Beroe’s engineering and analytics groups.

You will own onboarding, mapping of data sources, and the high-level configuration required to enable MAX features for each customer’s procurement environment. You will shape integration approaches (APIs vs SFTP, batch vs real-time), review engineering outputs, and guide data transformations and validation.

Qualificações

• 8–15 years in enterprise procurement technology, with hands-on experience across ERP and CLM
• Experience leading technical onboarding and integration for multiple customers at scale
• Ability to translate customer data, master data, and integration needs into product configurations

Responsabilidades

• Owns the technical onboarding for MAX customers and maps ERP, CLM, spend analytics, supplier master, contract repository and data warehouse.
• Shops the high-level configuration for signal sources, taxonomy alignment, and data ingestion requirements.
• Designs integration approaches with customer IT (APIs vs SFTP, real-time vs batch) and creates technical specs for data ops.
• Reviews engineering deliverables, challenges timelines, and validates scope against customer needs.
• Leads onboarding across product tooling, connectors, and mapping workbench; escalates features that require productization.

Conhecimentos

Solution architecture

Data integration

ETL

Python

SQL

Stakeholder facilitation

Enterprise procurement

Formação

Bachelor's degree in CS/Engineering or related field

Ferramentas

SAP Ariba

Coupa

Ivalua

Zycus

GEP

SAP S/4 HANA

Descrição da vaga

Solutions Architect, MAX.

Translator and architect between customer tech teams and Beroe.

What this role exists to do

Owns the technical relationship with each MAX customer once they sign. Bridges the customer's IT, data, and procurement-systems teams with Beroe's engineering, data, and analyst teams. Runs the technical onboarding — understands the customer's tech stack, shapes how MAX connects into it using the platform's pre-built connectors and tooling, and shapes the high-level configuration choices that make MAX work for that customer's category mix and procurement maturity. The role is built to be repeatable — onboarding many customers off a standard playbook and product tooling, however each customer will have their own nuances related to data that needs to be accommodated during data ingestion process to ensure all (or most) of MAX’s features could be effectively enabled.

What they actually do

• Technical discovery. Run technical onboarding workshops. Map the customer's ERP, CLM, spend analytics, supplier master, contract repository, and data warehouse. Understand their data quality and master-data fragmentation Highlight the impact on product features basis data (and quality thereof) received from the customer
• Configuration choices. Make the high-level configuration choices for the customer — which external and internal signal sources are switched on, alignment to customer taxonomy, etc.
• Integration design decisions. Shape the integration approach jointly with the customer's IT team — APIs vs SFTP, batch vs real-time, which pre-built connectors to switch on. Translate the decisions into a clear specification that the will guide the data ops team to setup MAX for success.
• Direct and challenge engineering. Scripting and data transformations are built by the Beroe Data Engineering Team. The Solutions Architect specifies what's needed, reviews what's delivered, and is technically credible enough to challenge engineering on scope, effort, and timelines rather than accepting estimates at face value.
• Put product tooling to work. Run onboarding through MAX's product capabilities — pre-built connectors, the mapping workbench, and migration and validation tools — for a first few customers though it will have to be done manually. Where a need recurs across customers, route it back to product as a feature request instead of solving it by hand each time.
• Own data readiness. Be accountable for getting ingested data complete, correctly mapped, and clean enough for MAX's LLM and insight layer to reason over before anything surfaces to the customer. Direct the data analysts who do the mapping, classification, deduplication, and validation, and sign off on the result.
• Customer technical contact. Be the named technical escalation point for the customer during onboarding and build. Resolve issues without pulling Beroe Engineering into customer calls wherever possible.
• UAT and enablement. Walk the customer's CM/CPO team through MAX as Evaluators come live. Train customer-side champions. Walk them through all the test scripts during UAT. Hand off to customer success into go-live.
• Steady-state ownership. After go-live, run quarterly technical reviews with the customer's tech leadership.
• Feedback loop into product. Feed customer learning back into MAX's roadmap. Distinguish between pattern-level needs (become product features) and customer-specific quirks (stay in configuration).
• Scale and team leadership. Standardize onboarding into a repeatable playbook so the model scales to dozens or hundreds of customers, not a handful of bespoke builds. As customer count grows, build and lead a small team of onboarding architects — shifting from running onboarding personally to running the function, and flagging recurring manual work so it can be productized and the team kept lean.

What they don't do

• They don't write production code (engineering does).
• They don't hand-build connectors, data pipelines, transformations, or migration scripts — those are productized engineering capabilities, not per-customer manual work (product and engineering own them).
• They don't run the product roadmap (product management does).
• They don't drive procurement category strategy or doctrine authoring (product management does).
• They don't run the customer's commercial relationship (customer success / commercial does).
• They don't lead pre-signature pitches (customer Success/commercial does).
• They don't do the day-to-day data-cleansing and mapping by hand — the data analysts do that, under the Solutions Architect's direction.

The kind of person we're looking for

• 8–15 years in enterprise procurement technology, with deep hands-on experience at one or more of: SAP Ariba, Coupa, Ivalua, Jaggaer, Zycus, GEP, SAP S/4 procurement.
• Has been the technical lead on at least five enterprise procurement-system implementations at scale.
• Conversant across master data management, CLM, and integration concepts — APIs vs SFTP, batch vs real-time, data ingestion through ETL, mapping and transformation — enough to make educate to the customer the impact on features basis the type / richness of data made available by customers
• Technically credible enough to review engineering's deliverables and challenge effort and timeline estimates, while leaving the build to them.
• Comfortable owning data-quality outcomes and directing analysts through mapping, classification, and validation work.
• Reads code (Python, SQL) but doesn't need to write production code.
• Strong workshop facilitation and architecture documentation skills. Bilingual fluency between procurement business language and IT/data engineering language.
• Profile typical comes from procurement-tech vendors (Coupa, Ariba, Ivalua, Zycus) or a Big-4 procurement-technology practice.
• Able to grow into a team lead — comfortable building and managing a small onboarding team as customer count scales, not only delivering hands-on.
• Industry depth in F&B, Beverages, Pharma, or Chemicals is a plus.