About The Role

In this role, you will design and deliver end-to-end data architectures on Azure for enterprise-scale data platforms and translate business needs into scalable, secure, and high-performance data solutions.

Responsibilities

Lead architecture design and decision-making, defining standards, patterns, and best practices
Collaborate with stakeholders to drive requirements gathering, data modeling, and solution design
Support and guide engineering teams in implementing data pipelines and platform components
Contribute to pre-sales activities, including workshops, solution envisioning, and proposal creation
Build and evolve data platforms, including ingestion, transformation, storage, and serving layers
Ensure data governance, quality, and security standards across the platform
Participate in the full project lifecycle, from PoC through MVP to full-scale implementation
Explore new technologies, build prototypes, and contribute to the Big Data community

Requirements

Hands-on expertise in building large-scale data platforms, migrations, and decision-support systems




Knowledge of designing and implementing modern data architectures (DWH, lakehouses, streaming, real-time, event-driven processing)
Experience with Azure data ecosystem, including services such as Microsoft Fabric, Azure Synapse, Data Factory, ADLS Gen2, Cosmos, Azure SQL, Databricks, and Azure Stream Analytics
Familiarity with SQL and Python (PySpark) for designing and optimizing data solutions
Experience in translating business requirements into scalable architecture and implementation roadmaps
Openness for acting as a customer-facing consultant, presenting architecture decisions, and leading technical discussions
Readiness for leading and mentoring data engineering teams, providing technical direction, and ensuring best practices
Knowledge of data governance, security, and data management frameworks across modern data platforms
Familiarity with streaming and real-time processing (e.g., Kafka,

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