Data Architect - Azure Platform (15-16 yrs)

Job Description :

We are seeking a seasoned Data Engineering & Analytics Architect with 15+ years of experience to lead and solutionize large-scale data modernization projects.

This role demands a strategic thinker and hands-on practitioner who can design, architect, and deliver cutting-edge data solutions on the Azure platform.

The ideal candidate will have strong leadership capabilities, a deep understanding of data architectures, and the ability to integrate AI-driven insights into data platforms.

Key Responsibilities :

Leadership & Strategy :

- Act as the primary advisor to customers, understanding their problem statements and recommending tailored strategies for data modernization and analytics.

- Lead cross-functional teams to design and implement scalable data platforms that align with business objectives.

- Drive discussions with executive stakeholders to ensure alignment of solutions with organizational goals.

- Mentor and coach teams on best practices, emerging trends, and new technologies in data engineering and analytics.

- Manage stakeholder expectations by communicating technical solutions in business terms and ensuring project delivery meets deadlines and budgets.

Solution Design & Architecture :

- Architect end-to-end data solutions on the Azure platform, including data lakes, warehouses, and real-time analytics.

- Develop enterprise-grade data models, schemas, and frameworks to support ingestion, transformation, and advanced analytics.

- Define and implement scalable, secure, and high-performance architectures using Azure Synapse Analytics, Azure Data Factory, Azure Data Lake, and Azure SQL Data Warehouse.

- Integrate AI capabilities into the data ecosystem, leveraging tools such as Azure Machine Learning, Databricks, and Cognitive Services for advanced analytics and insights.

- Ensure robust data governance, compliance, and security practices are embedded in all designs.

Implementation & Optimization :

- Lead the development of ETL/ELT pipelines for large-scale data processing, transformation, and storage.

- Optimize data pipelines, queries, and infrastructure to ensure reliability, scalability, and performance.

- Automate data quality checks and validations to maintain high data integrity.

- Monitor, troubleshoot, and resolve issues across data platforms.

AI & Advanced Analytics :

- Implement machine learning pipelines for predictive and prescriptive analytics using Azure Machine Learning and Databricks.

- Leverage Azure Cognitive Services to enable AI-powered functionalities such as natural language processing (NLP) and computer vision within data platforms.

- Drive the adoption of AI-based anomaly detection, forecasting, and recommendation systems within the data ecosystem.

Required Skills & Experience :

- Expertise in designing and implementing enterprise-scale data solutions using Azure services (Azure Synapse Analytics, Azure Data Factory, Azure Data Lake, Databricks).

- Experience with AI frameworks and platforms such as TensorFlow, PyTorch, Azure Machine Learning, and Cognitive Services.

- Strong experience in ETL/ELT processes, data modeling, and data pipeline optimization.

- Deep knowledge of Azure platform services, including cost optimization, scalability, and security best practices.

- Proficiency in Python, SQL, Spark, and other programming languages relevant to data engineering and AI.