1.
Data Pipeline Engineering & Integration
Design, implement, and maintain batch and near–real-time data pipelines from:
SAP ECC / S/4HANA (IDocs, extractors, CDS views, APIs),Salesforce CRM, Pricing and quoting platform, Multiple MES systems , External and third-party data sources
Implement ETL/ELT pipelines using enterprise-approved tools and cloud services
Ensure reliable orchestration, monitoring, error handling, and recovery of data flows
Optimize performance, scalability, and cost efficiency of data ingestion processes
2.
Enterprise Data Platform Development
Build and operate enterprise data platforms such as:
Cloud data warehouses / data lakes MS Azure and SAP Business Data Cloud or related data product,SAP BW / analytics backends,
Implement data models (raw, curated, semantic layers) aligned with:
Enterprise canonical models
Business domains (Sales, Finance, Operations, Manufacturing, Supply Chain)
Enable analytics, reporting, AI/ML, and self-service BI use cases
3.
Data Quality, Reliability & Observability
Implement data quality controls, validation rules, reconciliation checks, and alerts. Monitor data freshness, completeness, accuracy, and consistency
Support root cause analysis for data issues across source systems and pipelines
Ensure SLAs are met for business-critical datasets
4.
Data Governance & Security Implementation
Enforce data governance standards defined by the Enterprise Data Architect, including:
Data ownership and stewardship models,Master data alignment (customer, product, pricing, supplier)
Metadata, lineage, and documentation standards
Implement security, privacy, and compliance controls:
Role-based access control (RBAC),Data masking and encryption,GDPR and regulatory requirements
Support audits and compliance assessments related to enterprise data
5.
Collaboration with Enterprise Architecture & Stakeholders
Work closely with the Enterprise Data Architect to:
Translate architecture blueprints into implementable solutions,Contribute to roadmap execution and platform evolution
Application teams (SAP, Salesforce, MES)
Integration teams (e.g., MuleSoft, SAP BTP Integration Suite)
Analytics, BI, and Data Science teams
Business stakeholders and process owners
Provide technical input to project design, demand intake, and solution reviews
6.
DevOps, Automation & Best Practices
Apply DataOps and DevOps practices:
Infrastructure-as-code (IaC) where applicable
Version control and automated testing
Document pipelines, models, and operational procedures
Continuously improve reliability, performance, and maintainability