SAP BDC & Databricks Consultant

We are seeking an experienced SAP BDC & Databricks Consultant  to support an enterprise SAP Business Data Cloud (BDC) Proof of Concept (PoC).

The ideal candidate will have strong hands-on implementation experience with SAP Business Data Cloud, SAP Databricks, and SAP Datasphere, combined with expertise in AI/ML, data engineering, data integration, and solution architecture.

The candidate will be responsible for guiding architecture decisions, designing AI/ML use cases, establishing implementation best practices, and serving as the technical point of reference during the PoC.

The role requires a strong combination of SAP data platform expertise + Databricks AI/ML + customer-facing technical leadership.

Critical Mandatory Skills

Candidates must have hands-on experience with:

• SAP Business Data Cloud (BDC)
• SAP Databricks
• SAP Datasphere
• Databricks AI/ML
• Python / PySpark / Spark SQL
• MLflow
• Data Engineering
• AI/ML Model Lifecycle Management

Candidates should also have experience integrating SAP and non-SAP data sources.

Key Responsibilities

SAP BDC & Datasphere

• Design and implement solutions using SAP Business Data Cloud (BDC).
• Work with SAP BDC and Datasphere data products to prepare data for AI/ML workloads.
• Define architecture and implementation patterns for SAP BDC PoCs and enterprise implementations.
• Support data integration between SAP and non-SAP systems.
• Develop scalable data architectures aligned with enterprise standards.

SAP Datasphere

Strong working knowledge of:

• Data Modeling
• Replication Flows
• Transformation Flows
• Data Products
• BDC Connect
• Delta Sharing
• Design and optimize data models for analytics and AI/ML workloads.
• Support data ingestion, transformation, and preparation activities.
• Ensure data is appropriately structured for downstream Databricks processing.

Databricks Architecture & AI/ML

• Design and implement AI/ML use cases using Databricks.
• Lead:
• Model Development
• Experimentation
• Model Validation
• Model Deployment
• Provide technical guidance on Databricks architecture.
• Optimize Databricks solutions for:
• Performance
• Scalability
• Governance
• Reliability
• Design scalable data pipelines supporting machine learning workloads.
• Establish best practices for data engineering and AI/ML productionization.

Databricks AI/ML Skills

Strong hands-on experience with:

• Python
• PySpark
• Spark SQL
• MLflow
• Databricks
• Delta Lake
• Feature Engineering
• Model Training
• Model Evaluation
• Model Tuning
• Model Deployment

Machine Learning & Analytics

Experience with:

• Predictive Analytics
• Time-Series Forecasting
• Feature Engineering
• Model Development
• Model Training
• Model Evaluation
• Model Optimization
• Model Deployment
• ML Lifecycle Management
• Design practical AI/ML solutions based on business requirements.
• Evaluate appropriate machine learning approaches for enterprise use cases.
• Support the transition of AI/ML models from experimentation into production.

Data Engineering

• Build scalable data pipelines for AI/ML workloads.
• Design data ingestion and transformation processes.
• Work with structured and enterprise data sources.
• Integrate SAP and non-SAP data platforms.
• Optimize data processing and pipeline performance.
• Implement appropriate data governance and security practices.
• Work with Delta Lake and Databricks data engineering capabilities.

SAP & Enterprise Data Integration

Experience integrating SAP and non-SAP data sources, including:

• SAP S/4HANA
• SAP Datasphere
• SAP Business Data Cloud
• SAP Analytics Cloud (SAC)
• SAP CDS Views
• Finance Analytics
• FP&A Data
• Design integration patterns between SAP platforms and Databricks.
• Support enterprise data flows for analytics and AI/ML workloads.
• Understand SAP business data and its transformation into analytical/ML-ready datasets.

Finance & Analytics Use Cases

Experience with one or more of the following is preferred:

• Finance Analytics
• FP&A
• Forecasting
• Predictive Analytics
• SAP S/4HANA Finance
• SAP CDS Views
• SAP Analytics Cloud
• Translate finance and business requirements into practical AI/ML solutions.
• Support forecasting and predictive analytics use cases.
• Collaborate with Finance and SAP teams to identify high-value AI/ML opportunities.

PoC Leadership

• Lead the technical implementation of the SAP BDC Proof of Concept.
• Independently drive technical architecture and implementation decisions.
• Define recommended implementation patterns for future enterprise scale-up.
• Identify technical risks, dependencies, and architecture considerations.
• Demonstrate AI/ML capabilities to business and technical stakeholders.
• Mentor customer teams on Databricks, AI/ML, and data engineering best practices.
• Serve as the primary technical point of reference for AI/ML during the PoC.

Customer-Facing Technical Leadership

• Work directly with customer SAP, BDC, Finance, Data, and Technology teams.
• Translate business problems into practical technical solutions.
• Lead technical discussions and architecture workshops.
• Present solution options, recommendations, and trade-offs.
• Provide technical guidance throughout the PoC.
• Mentor customer resources and promote best practices.
• Clearly communicate complex AI/ML and data architecture concepts to technical and business audiences.

Required Qualifications

• 6–8 years of relevant experience.
• Strong hands-on SAP Business Data Cloud (BDC) implementation experience.
• Strong hands-on SAP Databricks implementation experience.
• Good working knowledge of SAP Datasphere.
• Strong Databricks AI/ML experience.
• Expert-level Python / PySpark / Spark SQL.
• Hands-on MLflow experience.
• Strong understanding of ML model lifecycle management.
• Experience with predictive analytics and/or time-series forecasting.
• Strong data engineering and pipeline development experience.
• Strong understanding of Databricks architecture and Delta Lake.
• Experience integrating SAP and non-SAP data sources.
• Customer-facing solution architecture / technical leadership experience.
• Ability to independently lead a technical PoC.
• Strong communication and stakeholder management skills.

Preferred Qualifications

• Experience with SAP Analytics Cloud (SAC).
• Experience with SAP S/4HANA.
• Experience with SAP CDS Views.
• Finance / FP&A analytics experience.
• Forecasting or predictive analytics experience.
• Experience with enterprise SAP BDC implementations.
• Experience with large-scale Databricks implementations.
• Experience mentoring customer teams.
• Experience transitioning PoCs into production implementations.