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: 5-8 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 2:00 am - IST PTO : 18 days/year and 10 public holidays Important to have very good conversational skills in English