Data Engineer
Location: Germany, Netherlands, Romania, Spain, France, UK, Austria (remote)
Language: Business English
Contract: fulltime, indefinite
Company information:
As a global B2B FinTech software company, Serrala helps organizations automate their complex finance processes to stay ahead of the curve. With locations in Europe, North America and Asia, our 700+ employees are dedicated to servicing our customers in all industry sectors, from medium-sized companies to global players. Our customers represent 20% of Fortune 500 and 50% of DAX 30 enterprises.
Introduction of the position:
Serrala is building a unified Data Platform as the foundation for cross‑domain analytics and AI outcomes across Accounts Receivable, Accounts Payable, and Payments & Cash. While reference architectures and standards define what the platform should be, Serrala's ability to realize value depends on reliable, production‑grade implementation and operation.
The Data Engineer (Data Foundations for AI) is a core execution role responsible for turning architectural intent into secure, scalable, and trustworthy data pipelines and data products. This role is essential to ensure that data from SAP‑embedded products and cloud‑native SaaS systems is consistently ingested, normalized, governed, and made fit for AI and analytics consumption.
Your tasks:
Build & Operate Data Pipelines
• 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.
Implement the Standardized Data Stack
• 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.
SAP & Product Data Integration
• Implement data ingestion from SAP‑embedded products (SAP S/4HANA 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.
Data Quality, Validation & Governance
• 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.
Collaboration with Product & Platform Teams
Collaborate closely with Product Managers and Engineers across SAP‑embedded and SaaS products to:
• 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).
Operate the Platform in Production
• 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.
Your profile:
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/4HANA or ECC.
• Experience integrating data from SAP‑embedded systems and cloud-native SaaS products.
• Familiarity with streaming/CDC concepts (e.g., Kafka) and API-based ingestion.
• Solid understanding of data quality, validation, and data modeling best practices.
• Awareness of governance and compliance requirements (GDPR, SOC2, ISO) in enterprise environments.
• Practical knowledge of SAP Datasphere and/or SAP Business Data Cloud for data integration or analytics scenarios.
• Experience working in hybrid environments with customer-managed constraints.• Exposure to analytics or AI/ML consumption patterns (feature-ready datasets, telemetry data).
• Experience with observability, monitoring, and cost optimization for data pipelines.
Interested? Reach out to
[email protected] or
[email protected] or apply directly.
It’s time to become a Serralian…
Do you look forward to taking on exciting challenges in an expanding and innovative environment? We continuously improve the way we work, including modern and flexible working conditions, professional development as part of our LearnLab, joint team events such as monthly lunches, after work events, and the Serralian Base Camp. And yes, we also promote sports activities and provide organic fruit and refreshing beverages.
Next steps: Apply quickly and easily with your CV via our recruiting tool or directly via
[email protected]
Pro-Tip: Skip the cover letter and pitch us in 3 sentences why exactly you are the perfect match for our team!
[EEO Statement]
We are proud to be an equal opportunity workplace. We celebrate and support diversity by providing equal employment opportunities regardless of race, creed, color, religion, age, sex, national origin, disability or handicap, genetics, protected veteran status, sexual orientation, gender identity or expression, arrest record, or any other characteristic protected by federal, state or local laws.
[To all recruitment agencies]
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