Data Engineer - Data Foundations AI
Listed on 2026-05-31
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IT/Tech
Data Engineer
Data Engineer - 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
Serrala is the global leader in finance process automation. For over 40 years, we have been advancing the office of the CFO with our award‑winning suite of finance automation applications.
Our solutions 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, reflecting the trust we’ve built with a diverse global community.
Join us as we lead the future of finance automation!
Role Summary
Serrala is building a unified Data Platform to enable cross‑domain outcomes across Accounts Receivable, Accounts Payable, and Payments & Cash. The Data Engineer will be a core contributor to this platform, responsible for designing, building, and operating data pipelines and data models that land, normalize, and curate data from SAP‑embedded and SaaS products into a layered Bronze / Silver / Gold architecture.
The role focuses on reliable execution, data quality, and scalability within a hybrid reference architecture (cloud + customer‑managed realities), operating under strict governance and compliance requirements (GDPR, SOC2, ISO).
What You’ll Do- Implement robust data ingestion pipelines to land data into the Bronze layer with traceability, metadata, and data contracts.
- Develop Silver‑layer transformations to cleanse, normalize, and consolidate data across heterogeneous product semantics.
- Build Gold‑layer data products that are curated, well‑modeled, and ready for consumption by AI and analytics use cases.
- Ensure pipelines are reliable, observable, and designed for incremental evolution.
- Build data pipelines and transformations using Serrala’s standardized primary data stack (e.g., Azure, Databricks or Snowflake, depending on final choice).
- Apply platform standards, templates, and “golden path” patterns defined by the Data Platform Architect.
- Optimize pipelines for performance, scalability, and cost‑awareness.
- Implement data ingestion from SAP‑embedded products (SAP S/4
HANA based solutions) using approved integration patterns. - Work with SAP Datasphere and/or SAP Business Data Cloud for analytics, data sharing, or integration scenarios where applicable.
- Integrate data from cloud‑native SaaS products via APIs, CDC/streaming, and file‑based mechanisms.
- Ensure SAP clean‑core principles are respected by using non‑invasive data access patterns.
- Implement data quality checks, validation rules, and anomaly detection at each layer of the platform.
- Apply governance standards related to access control, encryption, retention, and auditability.
- Ensure datasets meet compliance expectations for GDPR, SOC2, and ISO by design, not as an afterthought.
- Define data contracts and schemas
- Align on business semantics
- Ensure new product features are “data‑platform ready”
- Work closely with AI platform and analytics teams to ensure data is fit for downstream consumption (e.g., consistent semantics, reliable freshness).
- Monitor pipelines, troubleshoot failures, and continuously improve reliability and performance.
- Contribute to documentation, runbooks, and operational best practices.
- Participate in reviews and improvements of platform standards and patterns.
- 4+ years of hands‑on experience as a Data Engineer in modern data platforms.
- Proven experience building and operating ETL/ELT pipelines and layered data architectures.
- Strong practical experience with at least one modern data stack (e.g., Azure Data Factory, Databricks, Snowflake, or equivalent).
- Hands‑on experience with SAP‑centric data landscapes, including SAP S/4
HANA or ECC. - Experience integrating data from SAP‑embedded systems and cloud‑native SaaS products.
- Familiar it…
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