Design and lead scalable, secure data architectures supporting supply chain platforms, analytics, reporting, and downstream applications. Define enterprise data models, integration patterns, governance standards, and cloud strategies using Azure and Databricks. Collaborate with engineering, architecture, and business teams to translate requirements into solutions, improve platform performance, and guide data modernization. Provide technical leadership, documentation, and oversight of data quality, lineage, metadata, security, and compliance.
This role is for one of Weekday’s clients
Min Experience: 8+ years
Location: India
JobType: full-time
We are looking for an experienced Data Architect – Supply Chain to design and implement scalable, secure, and high-performance data architecture solutions supporting supply chain operations and analytics. The ideal candidate will have strong expertise in Data Architecture, Azure, and Databricks, along with a solid understanding of enterprise data platforms and modern cloud technologies.
In this role, you will work closely with business stakeholders, data engineers, enterprise architects, and supply chain teams to translate business requirements into robust data solutions. You will play a key role in defining data models, architecture standards, integration patterns, governance frameworks, and technology strategies that enable data-driven decision-making across the supply chain.
Requirements
Key Responsibilities
- Design and implement scalable data architectures for supply chain data platforms, analytics, reporting, and downstream applications.
- Define enterprise data models, logical and physical data structures, data domains, and data integration patterns.
- Architect cloud-based data solutions using Microsoft Azure services and ensure scalability, reliability, security, and performance.
- Design and optimize data processing and analytics solutions using Databricks, including data lakehouse architecture and distributed data processing.
- Collaborate with data engineering teams to establish best practices for data ingestion, transformation, storage, orchestration, and consumption.
- Analyze complex business and technical requirements and translate them into effective architecture and solution designs.
- Establish standards for data quality, metadata management, lineage, security, access control, and governance.
- Work with cross-functional stakeholders to understand supply chain processes and identify opportunities for data modernization and optimization.
- Review existing data platforms and recommend improvements to architecture, performance, scalability, and maintainability.
- Provide technical leadership and architectural guidance to data engineers and development teams.
- Create architecture diagrams, technical documentation, data models, and solution design specifications.
- Ensure solutions align with enterprise architecture, cloud security, compliance, and data governance standards.
Must-Have Skills
- 8–12 years of experience in data architecture, data engineering, or related technology roles.
- Strong hands-on experience in Data Architecture and designing enterprise-scale data platforms.
- Strong expertise in Microsoft Azure and cloud-based data architecture.
- Extensive experience with Databricks, including lakehouse architecture, data processing, and analytics workloads.
- Strong understanding of data modeling, data warehousing, data lakes, ETL/ELT, and data integration concepts.
- Experience designing scalable and high-performance data solutions for complex enterprise environments.
- Strong understanding of data governance, security, quality, lineage, and metadata management.
- Excellent communication and stakeholder management skills with the ability to work across business and technical teams.
Good-to-Have Skills
- Experience working with SAP S/4HANA and SAP-related enterprise data.
- Hands-on knowledge of Azure Data Factory (ADF) for data integration and orchestration.
- Prior experience working with Supply Chain data, processes, and systems.
- Exposure to ERP, procurement, inventory, logistics, manufacturing, demand planning, or order management data.
- Knowledge of modern data engineering and cloud-native architecture patterns.
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