The Azure Senior Data Lead will be responsible for leading the design, development, and implementation of enterprise-scale data engineering solutions on Microsoft Azure. The role involves architecting scalable data pipelines, driving data platform modernization, ensuring data quality and governance, and providing technical leadership to engineering teams while delivering high-performance analytics solutions.

Technical Skills & Expertise :

Azure Data Platform :

- Azure Data Factory (ADF)

- Azure Databricks

- Azure Data Lake Storage (ADLS)

- Azure Synapse Analytics

- Azure SQL Database

- Azure Key Vault

- Azure Monitor

- Microsoft Azure Cloud Services

Data Engineering :

- ETL/ELT Pipeline Development

- Data Integration

- Data Transformation

- Batch & Incremental Data Processing

- Data Warehousing

- Data Modeling

- Data Migration

- Workflow Automation

Programming & Scripting :

- Python

- SQL

- Oracle PL/SQL

- PySpark

- Shell Scripting (Preferred)

Databases :

- Oracle

- SQL Server

- Azure SQL

- PostgreSQL (Preferred)

- Relational Database Management Systems (RDBMS)

Big Data & Analytics :

- Apache Spark

- Azure Databricks

- Data Lake Architecture

- Data Warehousing Concepts

- Analytics Engineering

- Performance Optimization

Data Governance & Security :

- Data Quality Management

- Data Governance

- Data Security

- Access Management

- Compliance & Regulatory Standards

- Metadata Management

DevOps & Version Control :

- Azure DevOps

- Git

- CI/CD Pipelines

- Agile Methodologies

Preferred Candidate Profile :

Data Engineering & Solution Design :

- Lead the end-to-end design and implementation of enterprise data engineering solutions on Microsoft Azure.

- Design scalable, reliable, and high-performance ETL/ELT pipelines using Azure Data Factory and Azure Databricks.

- Develop robust data integration frameworks for structured and unstructured data sources.

- Define architecture standards and best practices for enterprise data platforms.

Azure Data Platform :

- Build and optimize Azure-based data platforms using Azure Data Factory, Azure Databricks, ADLS, and Synapse Analytics.

- Design scalable data ingestion, transformation, and orchestration workflows.

- Optimize cloud resources for performance, scalability, and cost efficiency.

- Ensure seamless integration across Azure services and enterprise applications.

Data Processing & Optimization :

- Design efficient data models and transformation logic for large-scale datasets.

- Optimize SQL queries, Databricks workloads, and ETL performance.

- Troubleshoot production issues and improve data pipeline reliability.

- Implement monitoring, logging, and alerting mechanisms for data workflows.

Data Governance & Security :

- Implement enterprise data governance, security, and compliance standards.

- Ensure data quality, consistency, lineage, and integrity across data platforms.

- Manage access controls and data protection mechanisms.

- Support audit, regulatory, and compliance requirements.

Leadership & Collaboration :

- Provide technical leadership and mentorship to data engineers and development teams.

- Collaborate with business stakeholders, solution architects, analysts, and project managers to translate business requirements into scalable technical solutions.

- Conduct design reviews, code reviews, and technical assessments.

- Drive adoption of engineering best practices and continuous improvement initiatives.

Innovation & Continuous Improvement :

- Evaluate emerging Azure data services and modern data engineering practices.

- Recommend improvements in architecture, automation, and operational efficiency.

- Promote reusable frameworks and standardized development methodologies.

- Stay updated with evolving cloud technologies and analytics trends.

Mandatory Skills :

- 6 - 11 years of experience in Data Engineering with strong expertise in Microsoft Azure.

- Hands-on experience with Azure Data Factory (ADF) and Azure Databricks.

- Strong programming skills in Python, SQL, and Oracle PL/SQL.

- Experience designing and developing enterprise-scale ETL/ELT pipelines.

- Strong understanding of Azure Data Lake, data warehousing, and data modeling concepts.

- Experience with data governance, security, and compliance best practices.

- Excellent analytical, problem-solving, and stakeholder management skills.

- Experience leading technical teams and mentoring junior engineers.

Nice to Have :

- Experience with Azure Synapse Analytics and Microsoft Fabric.

- Hands-on experience with PySpark and Apache Spark.

- Knowledge of Delta Lake and Lakehouse Architecture.

- Experience with CI/CD implementation using Azure DevOps.

- Microsoft Certified : Azure Data Engineer Associate (DP-203).

- Exposure to Power BI, Azure Machine Learning, or AI-driven analytics solutions.