Help design, build and continuously improve the clients online platform.
Research, suggest and implement new technology solutions following best practices/standards.
Take responsibility for the resiliency and availability of different products.
Be a productive member of the team.
Requirements
Experienced Senior Data Architect / Data Engineering Lead with over 10 years of expertise in designing, building, and managing enterprise-scale data platforms.
Possess deep technical proficiency in Azure Databricks, Microsoft Fabric, Snowflake, and Power BI, and will lead large-scale data transformation, modernization, and analytics initiatives.
Strong combination of data architecture expertise, hands-on engineering capabilities, and the ability to collaborate effectively with business and technical stakeholders.
Design and implement scalable, secure, and high-performance data architectures using Azure Databricks, Microsoft Fabric, and Snowflake.
Architect modern data platforms, including Lakehouse, Data Warehouse, and Medallion architecture patterns.
Define and implement enterprise data governance, security, and compliance frameworks.
Develop enterprise data models using dimensional modeling techniques such as star and snowflake schemas.
Build, optimize, and maintain ETL/ELT pipelines using Azure Databricks (PySpark, Spark SQL), Azure Data Factory, and Microsoft Fabric Data Pipelines.
Develop and manage batch and real-time data processing solutions.
Implement CI/CD pipelines and automation for data engineering workflows.
Optimize data processing performance, scalability, and cost efficiency across platforms.
Design and manage enterprise solutions using Fabric Lakehouse, Fabric Data Warehouse, and Fabric Real-Time Analytics.
Develop interactive dashboards and enterprise-grade reporting solutions using Power BI.
Implement data governance and security controls, including Row-Level Security (RLS).
Optimize semantic models, data models, and DAX queries for performance and scalability.
Design and manage Snowflake data warehouse environments, including multi-cluster and virtual warehouse configurations.
Implement performance tuning and cost optimization strategies.
Enable secure data sharing and collaboration across teams.
Manage Snowflake security, including RBAC, masking policies, and access controls.
Lead, mentor, and guide data engineers, BI developers, and technical teams.
Collaborate with business stakeholders to translate functional requirements into scalable technical solutions.
Conduct architecture reviews and promote best practices across teams.
Drive enterprise data modernization and cloud transformation initiatives.
Strong hands-on experience with Azure Databricks (Delta Lake, PySpark, Spark SQL)
Expertise in Microsoft Fabric and Snowflake platforms
Advanced experience with Power BI, including DAX and data modeling
Strong understanding of Data Lake, Lakehouse, and Data Warehouse architectures
Advanced SQL and Python programming skills
Experience with API integrations and distributed data systems
Knowledge of DevOps practices, including Azure DevOps, Git, and CI/CD pipelines
Experience with cloud-native architectures, preferably on Microsoft Azure
Expertise in Medallion architecture and modern data platform design
Strong knowledge of dimensional modeling (Kimball methodology)
Experience implementing data governance and data security frameworks
Understanding of compliance standards such as GDPR
Familiarity with Master Data Management (MDM) concepts
Microsoft Azure certifications (e.g., Azure Data Engineer Associate)
Snowflake certification
Microsoft Fabric or Power BI certifications
Experience leading large-scale enterprise data transformation programs
Exposure to AI/ML integration using Azure Databricks
