Hire Data Engineers for SAP S/4HANA and Dynamics 365: Skills and Engagement Models

2026-06-22 · Source: Data Engineering on Medium · Field: Technology & Digital — Data Science & Analytics, Cloud Computing & IT Infrastructure, Artificial Intelligence & Machine Learning · Depth: Intermediate, long

Summary

SAP S/4HANA and Dynamics 365 are critical ERP and CRM solutions for businesses, generating vast amounts of data. Despite generating 2.5 million terabytes daily globally, many organizations struggle with effective data analytics and AI adoption due to gaps in data systems. The global data engineering market is projected to reach \$105.40 billion by 2026, with over 90% of AI/ML projects relying on robust data engineering pipelines. Data engineering involves designing, building, deploying, and maintaining comprehensive architectures for end-to-end data management, including automated ETL/ELT pipelines, central data storage (data warehouses, data lakes, data lakehouses), and integration of various tools like SQL, AWS, Azure, Power BI, and Apache Hadoop. Acquiring specialized data engineers with expertise in these platforms is crucial, with staff augmentation being highlighted as an efficient method to onboard talent within 72 hours to a week, offering cost-effectiveness and control.

Key takeaway

CTOs and COOs embracing advanced technologies for streamlining IT infrastructure and supporting real-time decision-making should prioritize hiring data engineers with specific expertise in SAP S/4HANA and Dynamics 365. Consider staff augmentation services to quickly fill skill gaps and integrate these critical ERP/CRM systems into a robust, centralized data architecture. This approach offers cost-efficiency and control, accelerating your organization's ability to leverage data for competitive advantage.

Key insights

Specialized data engineering expertise is crucial for integrating and optimizing data from SAP S/4HANA and Dynamics 365, often best acquired via staff augmentation.

Principles

• Data engineering bridges the gap between raw data and effective analytics.
• Centralized data architecture supports real-time, data-driven decision-making.
• Staff augmentation offers rapid access to specialized talent.

Method

Design, build, deploy, and maintain comprehensive data architecture, including automated ETL/ELT pipelines and central storage, integrating ERP/CRM data.

In practice

• Implement automated data pipelines for ERP/CRM data integration.
• Consolidate data into a central data warehouse or data lake.
• Utilize staff augmentation for rapid access to SAP/Dynamics data engineers.

Topics

• Data Engineering
• SAP S/4HANA
• Microsoft Dynamics 365
• Staff Augmentation
• ERP Data Integration
• Data Pipelines

Best for: Executive, Director of AI/ML, IT Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by Data Engineering on Medium.