Data Architect

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.

• 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.

• 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.

• 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.

• Data Architecture: Expertise in designing and implementing enterprise-scale data solutions using Azure services (Azure Synapse Analytics, Azure Data Factory, Azure Data Lake, Databricks).
• AI & Machine Learning: Experience with AI frameworks and platforms such as TensorFlow, PyTorch, Azure Machine Learning, and Cognitive Services.
• Data Engineering: Strong experience in ETL/ELT processes, data modeling, and data pipeline optimization.
• Cloud Expertise: Deep knowledge of Azure platform services, including cost optimization, scalability, and security best practices.
• Programming: Proficiency in Python, SQL, Spark, and other programming languages relevant to data engineering and AI.
• Leadership: Proven ability to lead large-scale projects, mentor teams, and manage stakeholder relationships.