Data Platform Architect - Data Foundations AI Job Conway area,Arkansas USA,IT/Tech

Position: Data Platform Architect - Data Foundations for AI (all genders)

Data Platform Architect - Data Foundations for AI (all genders)

Location: Remote or hybrid within one of the following countries:
Germany, Spain, Romania, Netherlands, Austria, UK, France

Contract: full time / indefinite

Language(s): English (C1/C2)

Serrala is the global leader in finance process automation. For over 40 years, we have advanced the office of the CFO with our award‑winning suite of finance automation applications that streamline all working‑capital related processes, including Order to Cash, Procure to Pay, Cash Flow Management, and Treasury, across both cloud and SAP environments. Our 10+ hubs across Europe, North America, and India support over 2,800 clients worldwide.

Role

Summary

Serrala is building a unified Data Platform to enable cross‑domain outcomes across Accounts Receivable, Accounts Payable, and Payments & Cash. The Data Platform Architect will own the target reference architecture and technical standardisation of our data foundation, designed as a hybrid reference architecture (cloud + customer‑managed realities) and implemented as a layered model with a strong focus on governance, security, and compliance (GDPR, SOC2, ISO).

What

You’ll Do

Architect the Serrala Data Platform (Hybrid Reference Architecture)

Define and evolve Serrala’s end‑to‑end data platform architecture across ingestion, storage, processing, catalog, governance, and consumption – explicitly designed for a hybrid world (Serrala‑hosted + customer‑managed constraints).
Establish architectural principles to shift analytical and AI workloads away from operational systems, reducing coupling to product databases and enabling scalable ML/AI consumption.

Standardise on a Primary Stack (and make it production‑grade)

Lead evaluation and decisioning to standardise on one primary data stack (e.g., Azure, Databricks, Snowflake, etc.), then define the “golden path” implementation patterns, reference components, and templates.
Translate today’s heterogeneous landscape (SAP, SQL, No

SQL, time‑series, cloud storage, varied access methods) into a coherent target architecture and migration approach.

Deliver the Unified Bronze/Silver/Gold Foundation (AR/AP/Payments)

Design the layered data model for AR, AP, Payments & Cash:
Bronze (raw ingestion with traceability and contracts), Silver (cleansing, normalisation, consolidation across product semantics), Gold (curated domain‑ready data products and consumption models).
Drive a pragmatic “start building the bronze layer” execution approach, enabling early value while keeping long‑term platform integrity.

Data Governance, Security, and Compliance by Design

Define governance controls addressing GDPR, SOC2, ISO requirements through access control patterns (RBAC/IAM), encryption expectations, auditability.
Implement data classification and retention strategies adaptable to customer‑managed variations.
Maintain consistent compliance guardrails across products and regions.

Integration Patterns for Serrala’s Reality (SAP + SaaS + Streaming)

Define ingestion and integration patterns for SAP landscapes and interfaces (CDS‑Views, OData Services, SAP BTP, SAP Datasphere, SAP Business Data Cloud) and product APIs, CDC/streaming (Kafka).
Support bidirectional data share where needed.

Technical Leadership & Enablement

Act as technical authority for platform decisions: run architecture reviews, publish standards, mentor engineers, and ensure consistent implementation across squads.
Partner closely with Product Managers, Engineers, and AI platform/agent teams to ensure the data platform is fit for downstream AI use and analytics.

Required Experience & Skills

8+ years in data engineering or platform architecture, with several years owning end‑to‑end platform design.
Strong knowledge of at least one major modern data stack (Azure, Databricks, Snowflake or similar) and ability to lead standardisation.
Experience with hybrid integration constraints (customer‑managed environments, mixed regions, varied access methods).
Hands‑on experience with SAP‑centric data landscapes, including SAP S/4

HANA environments.
Practical knowledge of SAP Datasphere and/or SAP Business Data Cloud for analytics, data sharing, or integration…