Responsibilities: Key Responsibilities
Data Architecture & Strategy
- Define and drive enterprise data architecture strategies aligned with business objectives and technology roadmaps.
- Design scalable, secure, and high-performance data platforms leveraging Microsoft Fabric, Azure, and Databricks ecosystems.
- Establish architecture standards, best practices, reusable design patterns, and governance frameworks for enterprise data solutions.
- Lead cloud data modernization and migration initiatives from legacy platforms to cloud-native architectures.
- Create architecture blueprints, reference architectures, and implementation roadmaps.
Microsoft Fabric Leadership
- Architect and implement end-to-end solutions using:
- Microsoft Fabric Lakehouse
- Fabric Data Warehouse
- Data Pipelines
- Real-Time Analytics
- OneLake
- Power BI Integration
- Design Medallion Architecture (Bronze, Silver, Gold layers) within Microsoft Fabric.
- Drive Fabric deployment strategies, performance optimization, and environment governance.
- Implement Fabric security, access controls, lineage, monitoring, and data lifecycle management.
Azure Data Platform Architecture
- Design and implement enterprise data solutions using:
- Azure Data Factory (ADF)
- Azure Data Lake Storage Gen2 (ADLS)
- Azure Synapse Analytics
- Azure Key Vault
- Azure Event Hub
- Azure Functions
- Azure DevOps
- Define ingestion, transformation, storage, and consumption frameworks.
- Drive cloud adoption and optimization initiatives.
Databricks & Big Data Engineering
- Architect and optimize Databricks Lakehouse solutions.
- Lead implementation of:
- Apache Spark
- PySpark
- Delta Lake
- Unity Catalog
- Databricks Workflows
- Auto Loader
- Delta Live Tables
- Design large-scale data pipelines supporting batch and real-time workloads.
- Optimize Spark processing, cluster utilization, and workload performance.
Data Governance & Security
- Define enterprise data governance standards.
- Implement metadata management, lineage, cataloging, and data quality frameworks.
- Partner with security teams to ensure data privacy, compliance, and regulatory adherence.
- Enable business-friendly data discovery and self-service analytics.
Stakeholder Engagement
- Collaborate with business leaders, product owners, engineering teams, and program stakeholders.
- Translate business requirements into scalable technical architectures.
- Lead architecture reviews, design workshops, and solution governance forums.
- Provide technical leadership and mentorship to data engineering teams
Qualifications: Required Qualifications
- Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or related field.
- Minimum 10 years of experience in Data Engineering, Data Architecture, or Data Platform leadership roles.
Strong experience designing and architecting data solutions in cloud environments.
-
Must-Have Technical Skills
Microsoft Fabric
- Fabric Lakehouse
- Data Warehouse
- OneLake
- Data Pipelines
- Fabric Security & Governance
- Real-Time Analytics
- Power BI Integration
Microsoft Azure
- Azure Data Factory (ADF)
- Azure Data Lake Storage (ADLS Gen2)
- Azure Synapse Analytics
- Azure Key Vault
- Azure Functions
- Azure Event Hub
- Azure DevOps
Databricks
- Azure Databricks
- Delta Lake
- Unity Catalog
- Databricks Workflows
- Delta Live Tables
- Auto Loader
Data Engineering
- Apache Spark
- PySpark
- SQL
- Python
- Data Modeling
- ETL/ELT Design
Architecture & Governance
- Medallion Architecture
- Lakehouse Architecture
- Data Mesh (Preferred)
- Data Governance
- Metadata Management
- Data Lineage
- Data Quality Frameworks
- CI/CD & DevOps Practices