Position Summary The SAP BDC Engineer/Expert at Dassian Inc. will design, build, and operate data integration and analytics solutions on SAP Business Data Cloud (BDC), unifying data from SAP and non-SAP sources to power trusted, governed data products and AI-driven insights. This role builds Dassian's standard BDC-based product as a reusable, extensible core architected so that our Professional Services team can build additional customer-specific reports and AI Agents on top of it without compromising upgradeability or data governance. The role combines hands-on data engineering with deep functional knowledge of the SAP data and analytics landscape including Datasphere, SAP Analytics Cloud (SAC), data product modeling, replication flows, and analytics consumption to help Dassian's customers and internal teams turn enterprise data into reliable, actionable outcomes. Key Responsibilities 1. BDC Architecture & Data Product Development Design, provision, and configure SAP Business Data Cloud components to support Dassian's standard product and analytics use cases. Build and maintain data products and semantic models within SAP Datasphere and BDC as a reusable, versioned core, ensuring consistency, reusability, and business relevance across customers. 2. Data Integration & Pipeline Engineering Build and maintain replication flows, transformations, and data pipelines to move and reshape data from SAP source systems (e.g., S/4HANA) and external sources into BDC. Ensure pipelines are performant, resilient, and monitored, with clear ownership of data quality and freshness SLAs. Integrate BDC with complementary platforms (e.g., Databricks, SAP Analytics Cloud) to support advanced analytics and AI/ML workloads. 3. Product Extensibility & Professional Services Enablement Architect a clear separation between the standard product's core data model and its extension points, so Professional Services can build additional customer-specific reports without modifying or destabilizing the core. Define and document extensibility standards (naming conventions, versioning rules, approved extension patterns) so PS-built reports remain compatible across core product upgrades. Create reusable templates, sample data products, and starter reports that Professional Services can adapt for customer engagements. Provide enablement documentation, training sessions so Professional Services can self-serve most report-building needs, escalating only genuinely new platform capabilities to engineering. Establish a review/validation process for PS-built extensions to ensure they meet data governance, security, and performance standards before deployment to customers. 4. Data Governance & Security Implement data governance, access control, and compliance frameworks aligned with enterprise and regulatory requirements. Manage metadata, lineage, and cataloging to ensure trusted, well-documented data products across both the core product and PS-built extensions. Apply data security best practices, including sensitive data handling and licensing/entitlement management within BDC. 5. Analytics & AI Enablement Support integration with SAP Business AI / Joule and embedded analytics scenarios where applicable. Enable business intelligence and AI-powered analytics consumption through SAP Analytics Cloud and other downstream tools connected to BDC. Expose clean, governed data products that support machine learning and generative AI use cases. Evaluate and adopt AI-assisted development and data engineering tools to accelerate pipeline building, testing, and troubleshooting. 6. Cross-Functional Collaboration Work with Product Management, SAP functional consultants, and engineering teams to translate business and reporting requirements into BDC data models and pipelines. Act as the subject matter expert on SAP BDC for internal teams and customer-facing engagements, supporting solution design and troubleshooting. 7. Operations, Performance & Continuous Improvement Monitor platform health, pipeline performance, and cost efficiency, tuning configurations to optimize throughput and resource usage. Troubleshoot and resolve data integration, modeling, and connectivity issues across the BDC landscape, including issues arising from PS-built extensions. Stay current with SAP's BDC roadmap (Datasphere, SAC, Business Data Fabric, Joule, embedded AI) and proactively recommend adoption of new capabilities.

Qualifications Education:

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field (or equivalent practical experience).

Experience:

5+ years of experience in SAP data engineering, data warehousing, or analytics roles, including hands-on work with SAP Datasphere, BW/4HANA, or SAP Business Data Cloud. Experience integrating data from SAP source systems (S/4HANA, ECC) into a unified cloud data platform. Experience designing reusable, multi-tenant, or productized data models as opposed to one-off, project-specific pipelines is strongly preferred. Experience enabling non-engineering teams (e.g., Professional Services, consultants) to safely extend or configure a platform is a plus. Experience with data governance, metadata management, and security/compliance practices in enterprise data environments. SAP BDC certification (e.g., C_BCBDC) or equivalent hands-on platform experience strongly preferred.

Skills and Competencies:

Strong knowledge of SAP Business Data Cloud architecture, data product creation, and semantic modeling. Proficiency in building replication flows, transformations, and pipelines across SAP data sources. Ability to design extensible product architectures with clear boundaries between core and customer-specific customization. Strong documentation and enablement skills able to translate technical patterns into templates and training that non-engineering teams can use. Familiarity with SAP Analytics Cloud and downstream analytics/BI consumption of BDC data products. Working knowledge of complementary data platforms (e.g., Databricks) for advanced analytics and AI/ML integration. Understanding of data governance, lineage, licensing, and compliance frameworks within enterprise SAP landscapes. Comfort using AI-assisted engineering tools to accelerate data pipeline development, testing, and troubleshooting. Strong problem-solving and communication skills, with the ability to work across functional and technical stakeholders.

Pay:

$140,000.00 - $155,000.00 per year

Benefits:

401(k) 401(k) matching Dental insurance Employee discount Flexible spending account Health insurance Health savings account Life insurance Paid time off Professional development assistance Retirement plan Tuition reimbursement Vision insurance

Experience:

SAP BDC:

4 years (Required)

Work Location:

Hybrid remote in Scottsdale, AZ 85258