Job Summary
We are seeking an experienced Databricks Technical Architect to lead the architecture and modernization of enterprise Finance data and analytics capabilities.
The ideal candidate will bring strong expertise in Databricks, modern Lakehouse architecture, SAP financial data, enterprise integration, data governance, and Finance processes. This individual will work closely with Finance stakeholders, data engineering teams, enterprise architects, and technology teams to design and implement a scalable, governed, and high-performing data foundation.
Finance Data Architecture
- Partner with Finance stakeholders and business process owners to understand business processes, KPIs, reporting needs, and data requirements.
- Translate business requirements into scalable data architecture and technical roadmaps.
- Design data architecture supporting Finance domains such as:
- Accounts Payable
- Accounts Receivable
- General Ledger
- Record-to-Report
- Procure-to-Pay
- Order-to-Cash
- Fixed Assets
- Financial Close
- Cash Management
- Working Capital
- Identify opportunities to improve Finance operations through data, analytics, automation, and AI.
Databricks & Lakehouse Architecture
- Design and implement scalable Databricks Lakehouse architecture.
- Define architecture patterns for data ingestion, transformation, storage, data products, semantic models, and analytics consumption.
- Establish scalable patterns for batch and near-real-time data processing.
- Design solutions using Databricks, Delta Lake, Apache Spark, SQL, and modern data engineering practices.
- Optimize workloads for performance, scalability, reliability, and cost.
SAP & Enterprise Data Integration
- Design integration patterns between SAP systems and Databricks.
- Work with SAP ECC and/or SAP S/4HANA financial data.
- Define approaches for integrating SAP and other enterprise applications with modern data platforms.
- Establish authoritative data sources, data ownership, and data consistency standards.
- Partner with integration teams to implement scalable data replication and integration solutions.
Data Products & Analytics
- Define and develop governed Finance data products.
- Enable trusted data for reporting, analytics, forecasting, automation, and AI use cases.
- Establish common definitions for Finance KPIs and metrics.
- Support self-service analytics while maintaining governance and security controls.
- Enable advanced analytics, AI/ML, and GenAI initiatives using trusted enterprise data.
Data Governance & Architecture Leadership
- Define standards for data governance, metadata, lineage, data quality, security, and access controls.
- Establish data ownership and stewardship models for critical Finance data.
- Ensure architecture supports auditability, traceability, reconciliation, and financial controls.
- Develop target-state architecture, solution architecture, integration patterns, and technical roadmaps.
- Provide technical leadership and architecture guidance to engineering teams.
- Review solution designs to ensure alignment with enterprise architecture standards.
Required Qualifications
- 8+ years of experience in Data Architecture, Data Engineering, Enterprise Architecture, or related technology roles.
- Strong architecture and hands-on experience with Databricks and modern cloud data platforms.
- Strong expertise in:
- Databricks
- Lakehouse Architecture
- Delta Lake
- Apache Spark
- SQL
- Data Engineering
- Experience designing enterprise-scale data platforms and data products.
- Strong experience integrating SAP ECC and/or SAP S/4HANA data with modern data platforms.
- Good understanding of SAP Finance data, including SAP FI/CO and related financial processes.
- Strong knowledge of Finance processes such as AP, AR, GL, Procure-to-Pay, Order-to-Cash, and Financial Close.
- Experience with data governance, metadata, lineage, data quality, security, and access controls.
- Strong experience translating business requirements into scalable technical architecture.
- Excellent stakeholder management and communication skills.
Preferred Qualifications
- Databricks certifications.
- Experience with SAP S/4HANA Finance.
- Experience with SAP data replication or integration technologies.
- Experience with Azure, AWS, or Google Cloud Platform.
- Experience with APIs and enterprise integration architecture.
- Experience with Power BI or other enterprise analytics platforms.
- Experience supporting AI/ML or GenAI solutions.
- Experience with data mesh, data products, or domain-oriented architecture.
- Experience supporting financial controls, reconciliation, auditability, and reporting requirements.
Key Skills
Databricks | Lakehouse Architecture | Delta Lake | Apache Spark | SQL | PySpark | SAP ECC | SAP S/4HANA | SAP FI/CO | Finance Data | Data Architecture | Enterprise Data Architecture | Data Governance | Data Quality | Data Lineage | Metadata | Cloud Data Platforms | Enterprise Integration | Data Products | Analytics | AI/ML | GenAI