Azure Data Engineer Lead Noida

Azure Data Engineer (Lead)

Location: Bengaluru / Mumbai / Pune / Noida / Gururgram

Employment Type: Full time / Permanent

Experience Level: [ 8 12+ Years]

Mode: Hybrid

Job Summary

We are looking for a hands-on Azure Data Engineer (Lead) to lead a team of data engineers while actively contributing as an Individual Contributor. In this role, you will design, build, and maintain scalable data processing systems on the Azure platform. You will collaborate closely with data architects, data scientists, and business stakeholders to deliver robust, high-performance data solutions that drive business decisions.

Key Responsibilities

Technical Leadership & Hands-on Contribution: Lead, mentor, and guide a team of data engineers while actively writing code, designing pipelines, and building architecture.

Azure Data Platform Design: Design, develop, and maintain end-to-end data pipelines and data processing systems on Azure.

ETL & Data Integration: Build scalable ETL/ELT pipelines for seamless data ingestion, transformation, and storage from diverse sources.

Database Management & Optimization: Manage Azure data stores (Azure SQL, Cosmos DB, ADLS) and write highly optimized SQL queries for high performance.

Stakeholder Collaboration: Partner with data architects, data scientists, and business analysts to translate business requirements into technical data solutions.

Project & Delivery Management: Oversee data engineering project deliverables, ensuring code quality, performance, security, and timely execution.

Core Skills & Qualifications

Azure Mastery: Deep hands-on experience with Azure data services including Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure SQL Database, and Azure Cosmos DB (or Azure Synapse Analytics).

ETL & Data Pipelines: Proven expertise in designing, building, and optimizing production-grade ETL/ELT workflows and data integration processes.

Advanced SQL & Query Optimization: Expert-level SQL skills with a focus on database performance tuning, indexing, and query optimization.

Leadership Experience: Demonstrated track record of leading data engineering projects and mentoring engineering teams.

Data Modeling: Experience in relational and NoSQL data modeling, data warehousing concepts, and schema design. .