Azure Data Architect

Brief Description

We are looking for a highly experienced and innovative Azure Data Architect / Consultant to lead the design,

development, and deployment of enterprise-scale data platforms and AI-driven solutions. This role is critical in delivering

mission-critical data science, engineering, and analytics projects that support business transformation, operational

intelligence, and predictive decision-making.

The ideal candidate will have deep expertise in high-volume data processing, query optimization, and performance

tuning, ensuring that data pipelines and analytics workloads are efficient, scalable, and aligned with business goals. The

candidate will also lead Data and analytics initiatives using Microsoft platforms such as Microsoft Fabric, Azure Synapse,

Azure Machine Learning, Azure Data Bricks and other Data Engineering and Analytical tools.

Relevant Experience

• Experience in data engineering, data science, and analytics
• Proven experience in building and optimizing large-scale data pipelines and analytical models
• Hands-on experience (for minimum 3-4 years) with Azure data services in production environments
• Experience in enterprise data architecture, AI-led transformation, and real-time analytics

Key Responsibilities

• Architect, design, implement and maintain end-to-end data platforms using Microsoft Fabric, Azure Synapse Analytics,

Azure Data Factory, and Azure Databricks

• Design and lead data science and analytics projects using Azure Machine Learning, Python, and ML frameworks
• Build and optimize high-volume data pipelines with a focus on performance, scalability, and cost-efficiency
• Perform advanced query optimization, indexing, and performance tuning across structured and unstructured data

sources

• Enable real-time analytics and predictive insights using Azure Stream Analytics, Synapse Real-Time, and Power BI
• Define and implement data governance, security, and compliance strategies aligned with enterprise policies
• Provision and manage Azure Data Fabric components including Delta Lake, Azure Blob Storage, and Lakehouse

architecture

• Integrate data and AI solutions with internal and external systems using REST APIs, Azure Functions, Logic Apps, and

Event Grid

• Monitor and maintain data pipelines and analytics workloads using Azure Monitor, Log Analytics, and Application

Insights

• Collaborate with data scientists, analysts, and business stakeholders to align data solutions with strategic goals
• Mentor junior data engineers and scientists and contribute to internal data strategy and innovation forums
• The candidate will be hands on in solution and contributor to the project with active development and coding

deliverables.

• Initiate, lead and moderate meetings and discussions with internal as well as external stakeholders, leading to desire

outcome of the purpose of the project. If required travel for the meetings and discussion required.

Desired Skills

Azure Data Engineering and Analytics

• Azure Data Factory: ETL/ELT orchestration, data movement, and transformation
• Azure Databricks: Delta Lake, Spark, MLflow integration
• Azure Stream Analytics: Real-time data ingestion and processing
• Azure Data Lake Storage Gen2, Azure Blob Storage, Delta Storage

Data Science and Machine learning

• Programming: o Python, R, SQL, PL/SQL
• Libraries: Pandas, Scikit-learn, TensorFlow, PyTorch
• Model lifecycle management and integration with Azure ML pipelines

Data Analytics and Visualization

• Major Strength in PL / SQL and Procedural Queries.
• Extensive experience in working with RDBMS packages such as MS SQL, Oracle, PostgreSQL, etc.
• Power BI: Data modeling, DAX, real-time dashboards
• Synapse Real-Time Analytics: KQL queries, telemetry analysis
• Azure Monitor, Log Analytics, Application Insights

Integration and Architecture

• REST APIs, Azure Functions, Logic Apps, Event Grid
• Event-driven and serverless architecture patterns
• Real-time and batch data processing pipelines

Security and Governance

• RBAC, Managed Identities, Private Endpoints
• Data classification, lineage, encryption, and compliance

Nice to Have Skills

• Azure Machine Learning: Model training, deployment, monitoring, and MLOps
• Knowledge of Microsft Fabric and added benefit.
• Knowledge of ML Ops + Data Ops
• Experience with Azure AI Foundry and AI Studio
• Familiarity with Apache Kafka, Event Hubs, and streaming architectures
• Exposure to data mesh and data fabric principles
• Experience with CI/CD for data pipelines and MLOps and Data Ops
• Knowledge of multi-cloud data integration and hybrid data platforms