Azure Cloud Data Engineer

End-to-End Data Engineering

We’re looking for a hands-on Cloud Data Engineer who’s an expert in Python, PySpark, and SQL — with proven experience building end-to-end data pipelines on Azure using Data Factory, Synapse, and Databricks .

This role blends strong technical skills with sharp business understanding — ideal for someone who loves solving problems, designing scalable data solutions, and working closely with business teams.

Key Responsibilities :

End-to-End Data Engineering

Build and optimize data pipelines and ETL processes using ADF, Synapse, and Databricks .

Develop high-performance data transformations using Python, PySpark, and Advanced SQL .

Design and implement Lakehouse / Medallion architecture on Azure.

Create data models and Lakehouse to support analytics and BI initiatives.

Work directly with business stakeholders to gather requirements and translate them into scalable technical solutions.

Ensure data quality, governance, and performance optimization across large-scale datasets.

Customer Interaction & Technical Documentation

Interact with clients and business stakeholders to gather and analyze data requirements for building customized solutions.

Create clear and concise technical specification documents, detailing the architecture, data flow, and integration plans for project delivery.

CI / CD & Automation

Implement and manage CI / CD pipelines for data engineering projects, ensuring continuous integration and delivery of data processing and ETL jobs.

Automate data workflows and operationalize data processes, ensuring high performance and reliability.

Leadership & Mentorship

Lead and mentor junior data engineers, fostering a collaborative environment for learning and development.

Provide technical leadership and guidance throughout the project lifecycle, ensuring best practices are adhered to in all stages.

Required Skills & Experience :

Experience : 8-10 years in data engineering roles, with preferably at least 2 years in a lead role.

Azure Ecosystem : In-depth experience with Azure Data Factory, Azure Databricks, Azure SQL Data Warehouse, and Data Lake Storage.

Data Engineering Concepts : Strong understanding of end-to-end data engineering concepts, including ETL pipelines, data integration, and real-time data processing.

Dimensional Modeling & Data Warehousing : Solid experience with dimensional modeling and designing scalable data warehousing solutions.

Lakehouse Architecture & Medallion Architecture : Practical experience with implementing Lakehouse architecture and Medallion architecture patterns on Azure.

Security & Governance : Experience designing data governance frameworks, ensuring data security and compliance with industry standards.

CI / CD : Proficiency in setting up and maintaining CI / CD pipelines, automating deployment processes for data engineering.

On-prem & Cloud Databases : Experience with managing both on-premise and cloud-based large-scale databases, ensuring performance, security, and scalability.

Customer Interaction : Excellent communication skills with the ability to gather business requirements, create technical specs, and ensure stakeholder satisfaction.

Preferred Skills :

Certifications : Azure / AWS Data Engineer or similar certifications are a plus

Personal Attributes :

Problem-Solving : Strong analytical and troubleshooting skills.

Collaborative : Ability to work effectively with cross-functional teams and mentor junior engineers.

Detail-Oriented : Strong attention to detail with a practical approach to complex data engineering challenges.

Salary Range : Negotiable depending on experience and interview performance

Time Preferred : Night shift till 5 : 00 am - IST (This is a must and no exception - adequate compensation will be offered for the Night shift)

PTO : 18 days / year and 10 public holidays

Important to have very good conversational skills in English