Azure Data Architect

Job Title –

Job Nature –

Experience –

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

• 6–8 years of 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 mining 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

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

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

o Azure Data Factory: ETL/ELT orchestration, data movement, and transformation

o Azure Databricks: Delta Lake, Spark, MLflow integration

o Azure Stream Analytics: Real-time data ingestion and processing

o Azure Data Lake Storage Gen2, Azure Blob Storage, Delta Storage

Data Science and Machine learning

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

o Python, R, SQL, PL/SQL

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

o Model lifecycle management and integration with Azure ML pipelines

Data Analytics and Visualization

o Major Strength in PL / SQL and Procedural Queries.

o Extensive experience in working with RDBMS packages such as MS SQL, Oracle, PostgreSQL, etc.

o Power BI: Data modeling, DAX, real-time dashboards

o Synapse Real-Time Analytics: KQL queries, telemetry analysis

o Azure Monitor, Log Analytics, Application Insights

Integration and Architecture

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

o Event-driven and serverless architecture patterns

o Real-time and batch data processing pipelines

o Knowledge of ML Ops + Data Ops

Security and Governance

o RBAC, Managed Identities, Private Endpoints

o Data classification, lineage, encryption, and compliance

Nice to Have Skills

• 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

Soft Skills

• Strong analytical and problem-solving mindset

• Proactive, self-managed, and results-oriented

• Excellent communication and stakeholder engagement skills

• Team player with mentoring and leadership capabilities

• Curious, innovative, and eager to learn and share knowledge

• Strong project tracking and execution discipline

Academic Background and Qualifications

Bachelor’s or master’s 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

Deliverables

• Enterprise-scale data platforms and AI-driven solutions

• Optimized large-scale data pipelines and analytical models

• Real-time analytics and predictive insights

• Data governance, compliance, and security implementations

• Mentoring and technical leadership contributions

Interview Process

• The candidate may expect a scenario-based question and may be some assignment during or after the interview which has to be submitted by given timeline.

Work Location –

Notice Period –

Time Zone –

• India Time (IST) / European Time (CET/GMT) / Americas Time Zone (EST)