Azure Data Architect

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 :

1. Azure Data Engineering and Analytics :

- Microsoft Fabric : Data engineering, real-time analytics, and data science workloads

- Azure Synapse Analytics : Dedicated and serverless SQL pools, Spark pools, Synapse Pipelines

- 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

2. Data Science and Machine learning :

- Azure Machine Learning : Model training, deployment, monitoring, and MLOps

- Python, R, SQL, PL/SQL

- Libraries : Pandas, Scikit-learn, TensorFlow, PyTorch

- Model lifecycle management and integration with Azure ML pipelines

3. 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

4. Integration and Architecture :

- REST APIs, Azure Functions, Logic Apps, Event Grid

- Event-driven and serverless architecture patterns

- Real-time and batch data processing pipelines

- Knowledge of ML Ops + Data Ops

5. Security and Governance :

- RBAC, Managed Identities, Private Endpoints

- Data classification, lineage, encryption, and compliance.

Academic Background & Qualifications :

Bachelors or masters degree in computer science, Data Science, Engineering, (BE / ME Computer Science, Computer Science or IT , MCA).

Preferred : Postgraduate specialization or executive degree in AI/ML or Data Engineering.

Certifications (Mandatory any 2 of the below) :

- Microsoft Certified : Azure Data Engineer Associate.

- Microsoft Certified : Azure AI Engineer Associate.

- Microsoft Certified : Azure Solutions Architect Expert.

- Databricks certified Data Engineer Professional.

- Databricks certified Machine Learning Professional.