Sr Data Engineer SAP and AI Automation
Listed on 2025-12-23
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IT/Tech
Data Engineer, Data Analyst
Job Description
JOB SUMMARYThis role is responsible for delivering high-quality, governed, analytics-ready data products that support enterprise reporting, advanced analytics, and AI-driven use cases.
Beyond traditional data engineering, this position requires strategic thinking and strong business acumen. You will collaborate with product owners and business stakeholders to understand operational and commercial processes, translate data and diagnostic requirements into technical specifications, and communicate complex technical concepts back to non-technical teams in clear, accessible language. This role is supported by a strong ecosystem of IT and Analytics experts, including product owners, business relationship managers, data engineers, data architects, BI developers, data scientists, and platform specialists.
In addition to SAP data engineering, you will design, develop, and orchestrate AI-powered automation solutions to optimize workflows and processes within SAP environments. Your work will enable advanced analytics, intelligent automation, and seamless integration across enterprise systems.
KEY RESPONSIBILITIES Build & Operate SAP Datasphere Data Pipelines- Design and manage enterprise data pipelines within SAP Datasphere.
- Implement scalable ingestion using ODP, SLT, SDA/SDI, CDS extraction, APIs, and files.
- Engineer reliable delta handling, orchestration, and reconciliation.
- Build HANA-based analytical models and business-ready datasets.
- Develop semantic layers aligned to Finance, Supply Chain, Manufacturing, and Sales.
- Optimize models for SAC, Power BI, and downstream platforms.
- Develop transformations using Datasphere flows, SQL, and SQLScript.
- Manage Datasphere Spaces, compute allocation, access, and lifecycle.
- Architect virtualization vs replication strategies.
- Integrate SAP S/4
HANA and SAP BW on HANA datasets into Datasphere. - Leverage CDS Views, extractors, Open ODS Views, and BW Info Providers.
- Design hybrid SAP and non-SAP integration patterns.
- Implement validation, reconciliation, lineage, and metadata frameworks.
- Enforce security, PII masking, and regulatory compliance.
- Tune models, transformation logic, and analytical queries.
- Monitor performance, storage, and compute efficiency.
- Develop reusable automation frameworks using SQL, scripting, and SAP-specific tools to streamline data workflows and system integrations.
- Design and implement SAP automation solutions leveraging SAP Joule and AI-powered orchestration to optimize business processes and reduce manual effort.
- Integrate intelligent agents for predictive and prescriptive automation within SAP environments, enabling proactive issue resolution and process optimization.
- Support CI/CD pipelines, version control, and operational monitoring to ensure reliability and scalability of automation solutions.
- Deliver analytics-ready feature-engineered datasets.
- Partner with data science teams to support AI/ML pipelines.
- Work closely with product owners and business stakeholders to translate business requirements and diagnostic issues into technical solutions, and communicate technical concepts back in clear, non-technical language.
- Partner with SAP functional, architecture, and analytics teams.
- Mentor junior engineers and promote best practices.
- Perform additional duties as assigned.
The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. The work environment is a plant/office setting with varying degrees of temperatures and noise levels. Exposure to manufacturing equipment movement and wet/slippery floors. However, the vast amount of work is conducted in a climate-controlled office. Travel may be required.
PHYSICAL DEMANDSThe physical demands described here are representative of those that must be met by an employee to successfully perform the essential…
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