Job description

At Movado Group, we are committed to building the strongest brands in the industry - and we are passionate about what we do. Our people are fueled by a creative spirit and a drive for excellence that are reflected in every aspect of our business. We offer the watch industry a compelling strategic vision and track record of sustained growth - and we offer our employees unparalleled opportunities for career advancement. We invite you to come share in our success. Our people are the corner stone of our business - we invite you to grow your career with us. 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 accuracy and analytical value. Key Responsibilities 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. Plan milestones and deadlines and provide progress updates. Qualifications 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 The base salary range for this position is $150,000 to $170,000 per year. Base salary is determined by individualized factors such as experience and market location. Depending on company and individual performance, this position also may be eligible for an annual bonus.  As a benefit eligible position, this role enjoys access to our medical plans, dental plans, vision plan, Life Insurance, Accidental Dismemberment & Death Insurance, Tuition Reimbursement program, 401(k), Short-Term Disability, Long-Term Disability, Parental Leave, Legal Plan, Employee Assistance Program, Pet Insurance, Flexible Spending Account, Critical Illness Insurance, Watch Accommodations/Discounts, Paid Time Off and Company Paid Holidays! Benefits described above are subject to change and/or may be modified at the Company s discretion based on business needs or applicable laws. DIRECT APPLICANTS ONLY - NO AGENCIES Movado Group, Inc. designs, sources, and distributes MOVADO®, MVMT®, OLIVIA BURTON®, EBEL®, CONCORD®, COACH®, TOMMY HILFIGER®, HUGO BOSS®, LACOSTE®, and CALVIN KLEIN® watches worldwide, and operates Movado company stores in the United States. Movado Group, Inc. is an equal opportunity employer. It prohibits discrimination based on age, color, disability, marital or parental status, national origin, race, religion, sex, sexual orientation, gender identity, veteran status or any other legally protected status in accordance with applicable federal, state and local laws. #ZR #LI-MP1 Movado Group, Inc. is an equal opportunity employer. It prohibits discrimination based on age, color, disability, marital or parental status, national origin, race, religion, sex, sexual orientation, gender identity, veteran status or any other legally protected status in accordance with applicable federal, state and local laws.

Requirements

Must-haves

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. Plan milestones and deadlines and provide progress updates.

Nice-to-haves

Preferred: Master’s Degree or equivalent postgraduate qualification
Experience in offshore/onshore delivery models preferred

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

sqlpythonaiapiml

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave