Azure Cloud Data Engineer

End-to-End Data Engineering

hands-on Cloud Data Engineer

strong technical skills

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