Job Summary
To be responsible for managing technology in complex projects ,providing technical guidance and ensuring successful delivery of solutions.
Role : Data Engineer
Location : PAN India (Prefer Noida or HYD)
Band : E2.2
Experience : 6+ Years
Primary Skill : Azure Fabric, Azure Data Factory, Logic Apps.
Secondary Skill : Power Automate and Power BI
HR L4 : ERS CU-DE-Data (HDU)-Data Engineering
Number of positions : 2
Hiring Mode : FTE
BSD : 1st March 2026
Sell rate : /$30
Project : C285424 / BI_Azure_Finance_FY25
Job Details : We are seeking a highly skilled lead Data Engineer to join our growing data team. The ideal candidate will have hands-on experience in designing, developing, and maintaining scalable data solutions using Microsoft Azure services and will be responsible for building robust data pipelines, data integration workflows, and analytics platforms using Azure Fabric, Azure Data Factory, Logic Apps , Power Automate and Power BI.
Required Skills & Qualifications:
• Bachelor's or Master’s degree in Computer Science, Information Systems, or related field.
• Experience in data engineering or related roles.
• Experience with Azure Fabric, Azure Data Factory, and Logic Apps.
• Experience with Azure Fabric in managing microservices or data flows .
• Strong SQL and data modeling skills.
• Experience with Power BI for data
RM : 51948803
Key Responsibilities
2. To conduct comprehensive code reviews, establish and oversee quality assurance processes, performance optimization , implementation of best practices and coding standards to ensure successful delivery of complex projects.
3. To ensure process compliance in the assigned module| and participate in technical discussions/review as a technical consultant for feasibility study (technical alternatives, best packages, supporting architecture best practices, technical risks, breakdown into components, estimations).
4. To collaborate with stakeholders to define project scope, objectives, deliverables and accordingly prepare and submit status reports for minimizing exposure & closure of escalations.