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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Databricks Reporting Architect - **Company:** Movado Group Inc. - **Location:** Paramus, NJ, United States - **Salary:** $150,000.0 - $170,000.0 - **Contract:** Permanent contract - **Skills:** SAP Cloud, Query Performance, Artificial Intelligence, Audit Trail, Big Data, Software Quality, Information Systems, Data Architecture, Information Engineering, Data Governance, Data Visualization, Data Warehousing, Database Queries, Software Debugging, Middleware, Apache Hive, Python (Programming Language), Machine Learning, Open Data Protocol, Query Optimization, Power BI, SAP (Applications), SAP NetWeaver Business Warehouse, SAP NetWeaver Data Management, SAP Project System, SQL Databases, Data Streaming, Tableau (Software), Data Processing, Data Storage Technologies, Data Ingestion, GitHub Copilot, Apache Spark, Data Lakes, Pyspark, Information Technology, Data Lineage, Star Schema, Machine Learning Operations, Physical Data Models, Virtual Agents, Api Design, Data Pipelines, Databricks - **Published:** August 24, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/87714715/1 ## About the Role * Required: Bachelor's Degree in Computer Science, Engineering, Information Systems, or related field * Preferred: Master's Degree or equivalent postgraduate qualification * Minimum 7+ years of experience in data engineering, data warehousing, or analytics architecture * Minimum 3+ years of hands-on experience with Databricks, including Delta Lake, notebooks, and Jobs/Workflows * Strong proficiency in PySpark, spark SQL, and Python for large-scale data transformation * Proven experience designing and implementing Medallion Architecture (Bronze/Silver/Gold) in a production environment * Strong SQL skills for data modeling, query optimization, and reporting layer development * Demonstrated experience building dashboards and reports using Power BI, Tableau, or SAP Analytics Cloud * Experience with AI-assisted development tools (e.g., GitHub Copilot, Databricks AI Assistant) to accelerate data engineering work * Familiarity with SAP data structures and business processes (OTC, P2P), ability to understand data from SAP systems * Experience consuming data from middleware integration layers or data lake ingestion pipelines * Understanding of data governance concepts: Unity Catalog, data lineage, access control * Strong analytical, debugging, and problem-solving skills * Excellent communication and stakeholder management skills; ability to translate business requirements into technical solutions * Ability to work independently in a fast-paced, global environment * Experience in offshore/onshore delivery models preferred ## Description The Databricks Reporting Architect will be responsible for the hands-on design, development, and delivery of enterprise data solutions on the Databricks Lakehouse platform. This role is central to our strategic migration from SAP BW to a modern cloud data architecture, where data flows from SAP systems through middleware into Databricks. The architect will design and implement Medallion Architecture (Bronze/Silver/Gold) pipelines, build high-performance consumption layers, and deliver self-service dashboards and analytics. The role requires strong expertise in Apache Spark, PySpark, SQL, and Python, with a forward-looking approach to leveraging AI-assisted development tools to accelerate delivery. A key focus of this role is balancing platform performance with cost efficiency ensuring compute, storage, and query strategies are optimized for both speed and spend. Collaboration with business stakeholders, SAP functional teams, and data engineering resources is essential to ensure data, * Define how data flows from SAP source systems through middleware into the Databricks Lakehouse, establishing clear guidelines for Medallion Architecture (Bronze/Raw, Silver/Cleansed, Gold/Curated layers) * Build scalable transformation logic using PySpark and Spark SQL, ensuring data quality, performance, and reliability across all layers * Architect optimized storage layers using Delta Lake, ensuring efficient data layout via Z-Ordering, partitioning strategies, and liquid clustering for high-performance queries * Design and manage the Gold/consumption layer to serve reporting and analytics use cases with optimized query performance * Work with Delta Lake for ACID-compliant data storage, time-travel, schema enforcement, and incremental data processing * Translate complex business requirements into scalable physical data models, Dimensional/Star Schema, specifically optimized for Databricks SQL * Serve as the primary architect for data governance, implementing Unity Catalog to enforce fine-grained access control (row and column-level security), data lineage tracking, and centralized auditing * Design automated data quality validation pipelines using Delta Live Tables (DLT) or Great Expectations to ensure data trust across all layers * Implement data quality checks, validation frameworks, and monitoring across all pipeline stages; perform root-cause analysis on data discrepancies * Define and document Databricks architecture patterns, data models, and pipeline designs for reuse, auditability, and compliance * Collaborate with middleware and data engineering teams to consume SAP data (from ECC/S4) landing in Databricks via integration pipelines * Support OData or API-based integrations where data flows between SAP and Databricks; coordinate with upstream teams on data discrepancy resolution * Work with data visualization tools such as SAP Analytics Cloud or Power BI for reporting and analytics * Understand SAP data structures (OTC, P2P domain) to accurately model and transform business data - deep SAP BW development skills not required * Perform root-cause analysis on data discrepancies and resolve data quality issues in collaboration with upstream teams * Build and maintain dashboards and self-service reports for business stakeholders across OTC and P2P processes * Partner with business users to gather requirements, translate them into analytical models, and validate outputs * Actively leverage AI coding tools (e.g. Databricks AI Assistant, Claude) to accelerate development, generate transformation code, and improve code quality * Evaluate and apply emerging AI/ML capabilities available within the Databricks platform (e.g., MLflow, AutoML, Genie) for analytics use cases * Stay current with Databricks platform updates, Apache Spark developments, and modern lakehouse best practices * Support testing, validation, and deployment of solutions with minimal business disruption * Self-manage Business process improvements. 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