ME
metayb
Data Architect
Chennai 路 Director
Older listing - lower visibility likelyVerified listingPosted 79d ago
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Skills required
24 listedData Warehouse ArchitecturesAzure Data LakeAzure Data FactoryCI/CDValue CreationSAP ImplementationWorkflow AutomationVirtual Reality+16 more
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Job description
About Metayb
Metayb is a digital transformation company on a mission to transform seamlessly by empowering organisations to navigate the vast landscape of the digital-first era. We have grown into a close-knit family of 500+ employees, each possessing rich field expertise. Metayb focuses on fostering seamless customer experiences, enhancing operational efficiency, and deriving actionable insights. By harnessing the power of emerging technologies, Metayb aims to be the unparalleled choice for global customers, delivering strategic goals effectively within a digital-first ecosystem of value creation.
Our key areas of expertise lie in Digital Transformation, Data Science, SAP Implementation, Workflow Automation, Dashboarding, Visualization, Finance, and Supply Chain Services. We strongly aspire to venture into IoT, AI/ML, and Virtual Reality. Metayb endeavours to be best-in-class across digital solutions, infrastructure, and product engineering.
Role Overview
We are looking for an experienced Data Architect with extensive expertise in Microsoft Fabric, Azure Synapse Analytics, and Databricks to design and implement scalable, enterprise-grade data platforms. The ideal candidate will define data architecture standards, develop high-performance data solutions, and establish robust data governance frameworks while collaborating closely with business stakeholders, architects, data scientists, and engineering teams.
This role demands strong architectural capabilities, deep hands-on experience with modern cloud data platforms, and the ability to lead technical teams in delivering high-quality, secure, and scalable data solutions.
Key Responsibilities
馃敼 Data Architecture & Solution Design
- Design and define enterprise data architecture for modern cloud-based applications.
- Develop scalable data models, storage strategies, and integration architectures.
- Design data platforms using Microsoft Fabric, Azure Synapse Analytics, and Databricks.
- Build and maintain robust Lakehouse and Data Warehouse architectures.
- Establish enterprise data standards, architecture principles, and best practices.
馃敼 Data Engineering & Platform Development
- Design, develop, and optimise large-scale ETL/ELT data pipelines.
- Implement scalable data ingestion and transformation frameworks.
- Develop high-performance Spark workloads using Databricks or Microsoft Fabric.
- Optimise data processing workflows for performance, scalability, and cost efficiency.
- Handle large-scale structured and unstructured datasets efficiently.
馃敼 Data Modelling & Integration
- Design conceptual, logical, and physical data models.
- Build scalable dimensional models (Star & Snowflake Schemas).
- Implement data integration across multiple enterprise systems.
- Ensure data consistency, integrity, and quality across platforms.
- Design incremental loading strategies and data lifecycle management.
馃敼 Cloud & Modern Data Platform
- Work extensively with Azure Synapse Analytics, Microsoft Fabric, Azure Data Lake Storage, and Databricks.
- Develop data transformation logic using Python and PySpark.
- Implement Spark-based distributed processing solutions.
- Integrate cloud-native services to build modern analytics platforms.
- Support enterprise reporting and advanced analytics initiatives.
馃敼 Governance, Security & Quality
- Define and implement enterprise data governance frameworks.
- Ensure data quality, lineage, metadata management, and security standards.
- Establish best practices for data access, compliance, and governance.
- Develop technical documentation for architecture, processes, and standards.
- Promote reusable frameworks and continuous improvement across projects.
馃敼 Leadership & Stakeholder Management
- Act as the Subject Matter Expert (SME) for enterprise data architecture.
- Lead technical discussions and guide solution design across multiple teams.
- Mentor and support engineering teams on architecture best practices.
- Collaborate with architects, data scientists, analysts, and business stakeholders to translate business requirements into scalable technical solutions.
- Drive technical decision-making and contribute to strategic data initiatives.
Skills Required
- 12+ years of experience in Data Engineering, Data Architecture, or Cloud Data Platforms.
- Minimum 7.5 years of hands-on experience in Databricks.
- Bachelor's degree (15 years of full-time education) in Computer Science, Engineering, Information Technology, or a related field.
- Strong expertise in Microsoft Fabric, Azure Synapse Analytics, and Databricks.
- Excellent knowledge of data architecture, data modelling, and data warehousing concepts.
- Strong experience in designing and developing enterprise-scale ETL/ELT pipelines.
- Proficiency in Apache Spark, Python, and PySpark.
- Experience with Azure cloud data services and modern analytics platforms.
- Strong understanding of data integration, performance optimisation, and troubleshooting.
- Experience implementing data governance, security, and quality frameworks.
- Excellent communication and stakeholder management skills.
- Ability to lead technical teams and mentor engineers.
Technical Skills
- Strong expertise in Microsoft Fabric, Azure Synapse Analytics, and Databricks.
- Hands-on experience in designing and implementing scalable data architectures and modern data platforms.
- Proficiency in data modelling, data warehousing, and Lakehouse architecture.
- Strong experience in developing and optimising ETL/ELT pipelines using Apache Spark, PySpark, and Python.
- Expertise in Azure cloud data services, data integration, and orchestration.
- Solid understanding of data governance, security, metadata management, and performance optimisation.
- Experience handling large-scale enterprise data platforms and complex data processing workloads.
- Experience with Azure Data Factory, Azure Data Lake Storage (ADLS), and Azure SQL.
- Exposure to Microsoft Purview and enterprise data governance frameworks.
- Familiarity with Power BI, CI/CD pipelines, Git, and Azure DevOps.
- Knowledge of event-driven architectures, API integrations, and modern DevOps practices.
- Experience supporting AI/ML or advanced analytics data platforms.
Disclaimer: The job title mentioned in this description is generic and intended for broad categorization purposes. The final designation will be determined based on the candidate鈥檚 performance during the interview process, relevant experience, and alignment with the organizational hierarchy.
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