Lead Azure Data Engineer

This role is for one of the Weekday's clients

Salary range: Rs - Rs (ie INR 5-20 LPA)

Experience: 4+ yrs

Location: Bengaluru, Pune, Hyderabad, NCR, Chennai

Job Type: full-time

We are seeking a Data Engineer / Senior Data Engineer to design, build, and optimize large-scale cloud-based data platforms that support business intelligence, analytics, and data-driven decision-making. This role focuses on developing modern data pipelines, data lakes, and warehouse solutions while working with real-time and batch processing systems in a cloud environment. You will collaborate with cross-functional teams to deliver scalable, high-quality data architectures that enable actionable insights across the organization.

Requirements

Key Responsibilities

\n
• Design, develop, and maintain scalable ETL/ELT pipelines for processing large volumes of structured and unstructured data.
\n
• Build and manage cloud-based data platforms, including data lakes, data warehouses, and analytics solutions.
\n
• Develop and optimize data pipelines using Spark, PySpark, and cloud-native data services.
\n
• Work with real-time and batch data processing frameworks to ensure reliable and efficient data delivery.
\n
• Design robust data models and implement best practices for data quality, governance, and performance.
\n
• Optimize SQL queries, database performance, and large-scale analytics workloads.
\n
• Develop and maintain reporting and visualization solutions to support business stakeholders.
\n
• Collaborate with business, engineering, analytics, and product teams to define data requirements and solutions.
\n
• Support CI/CD processes, automation, monitoring, and deployment of data engineering solutions.
\n
• Create technical documentation and ensure adherence to modern engineering and data management standards.
\n

What Makes You a Great Fit

\n
• 7+ years of experience in Data Engineering, ETL development, and cloud-based analytics solutions.
\n
• Strong expertise in Azure Data Factory, Databricks, Azure Synapse Analytics, Spark, and PySpark.
\n
• Hands-on experience with data lakes, Delta Lake architecture, and modern big data technologies.
\n
• Strong SQL development, query optimization, and performance tuning skills.
\n
• Experience designing scalable cloud-hosted data platforms and enterprise-grade data architectures.
\n
• Knowledge of reporting and analytics tools, including data modeling and dashboard development.
\n
• Familiarity with CI/CD pipelines, DevOps practices, and cloud security concepts such as RBAC.
\n
• Strong problem-solving, communication, and stakeholder management skills.
\n
• Ability to translate business requirements into scalable technical data solutions while maintaining high standards of quality and reliability.
\n