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 in 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.

Please note : Must be ready to join within 2 weeks after the interview process is completed.

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: 3-5 years in data engineering roles, with preferably at least 2 years in hands on 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 must

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 3:00 am - IST (This is a must and no exception)

PTO : 18 days/year and 10 public holidays

Important to have very good conversational skills in English