**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** 

1) 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.

2) 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.

3) 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.

4) 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.

5) 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).

6) 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.

**Required Experience & Skills**

· 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.

**Nice-to-Have** 

· 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.

**Working Style / Mindset**

· You enjoy turning architectural intent into reliable, production-grade data pipelines.

· You care deeply about data quality, correctness, and trust.

· You collaborate pragmatically with product and platform teams to ship value incrementally.

· You treat governance, security, and compliance as part of engineering craftsmanship, not paperwork.

**Why you’ll love it here**

Step into a dynamic, agile workplace where continuous learning is championed by leadership, and innovation in finance automation is fuelled by cutting-edge tech, AI integration, and strategic SAP transformation. We partner with the best to stay ahead - so you can too.

At our core, we're **Reliable**, **Passionate**, **Empowering**, and **Enterprising** - committed to lasting customer and employee relationships, bold innovation, and your growth every step of the way.

**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.