Celebal Technologies
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Jaipur · On-site · 2-5 Yrs · Oct 9
Enterprise Software & Network Solutions · 201 to 500 Employees · Jaipur, India
Celebal Technologies is a premier software services company in the field of Data Science, Big Data and Enterprise Cloud. Celebal Technologies helps you to discover the competitive advantage by employing intelligent data solutions using cutting-edge technology solutions that can bring massive value to your organization. The core offerings are around "Data to Intelligence", wherein we leverage data to extract intelligence and patterns thereby facilitating smarter and quicker decision making for clients. Celebal Technologies solutions are powered by Robotics, Artificial Intelligence and Machine Learning algorithms which offer improved business efficiency in the interconnected world. Companies clients are Product ISVs and delivery organisations across the globe who use our niche expertise in product development as well as Enterprise project implementations. We have adopted the highest standards of service quality and operational excellence, enabling its clients across a wide range of industries to transform into a data-driven enterprise. Our tailor-made solutions help enterprises maximise productivity, improve speed and accuracy. Our adept team industry experts have strong expertise in various industry-standard technologies along with niche emerging areas including Blockchain, Analytics & Visualization, IoT, Chatbot, Data Science- AI & ML. We have hands-on experience in developing and performing supply chain analytics and media greenlighting solutions, connect the dots across data pits for generating actionable insights. We help modernize legacy and on-premise applications by leveraging modern cloud paradigms such as Microservices, Advance Analytics, API Management and other Cloud-native services. With Celebal Technologies, who understands the core value of modern analytics over the enterprise, we help the business in improving business intelligence and more data-driven in architecting solutions. Our analytics team caters to ad-hoc and defined business analytics
Hiring: Engineering
What employees say
+ Good projects and good expoy
− No wlb and no flexibility
More reviews on the company profile.
Interview experience · Data Scientist
I apply on walk in drive after waiting 2 hours my number were come the interviewer ask about gen ai and agentic ai question, I answered all question still not selected
Average difficulty · Noida · 304 reports
More interview insightsJob description
Overview
Azure Data Engineer(MS-Fabric)
Responsibilities
- Design and develop scalable ETL/ELT pipelines using Microsoft Fabric Data Factory, Dataflows Gen2, SQL, Python, and PySpark.
- Build and optimize Lakehouse, Warehouse, OneLake, and Delta Lake solutions using Bronze/Silver/Gold architecture.
- Develop complex T-SQL queries, views, transformations, and dimensional data models using star schema, fact/dimension tables, and SCD.
- Develop and optimize Power BI semantic models, DAX measures, Power Query, and reports.
- Implement and optimize Direct Lake models while minimizing unnecessary DirectQuery fallback.
- Design and maintain Fabric Data Agents and validate AI-generated SQL, Pyspark, and DAX using Copilot/Fabric AI capabilities.
- Perform end-to-end performance tuning across Spark/PySpark, SQL Warehouse, Delta tables, Data Factory, Power BI, DAX, and Fabric capacity.
- Optimize Delta tables using appropriate partitioning, OPTIMIZE, VACUUM, and V-Order strategies.
- Monitor workloads using Spark UI, Query Insights, Monitoring Hub, and Capacity Metrics.
- Implement CI/CD using Git/Azure DevOps/GitHub and Fabric deployment pipelines.
- Apply security and governance using Microsoft Entra ID, workspace roles, OneLake security, and Microsoft Purview.
- Collaborate with analysts, BI developers, data scientists, and business stakeholders to deliver production-ready data solutions.
Qualifications
- Job Summary
- We are looking for an experienced Azure Data Engineer with strong Microsoft Fabric expertise to design, develop, and optimize modern data and analytics solutions. The role requires hands-on experience across Fabric Lakehouse,Warehouse,OneLake,Data Factory, PySpark, Power BI, DAX, semantic models, and Data Agents.The ideal candidate should be strong in both data engineering and analytics, with a particular focus on performance optimization, scalable data modeling, and AI-enabled data solutions.
- 2-6 years of experience in Azure Data Engineering.
- Strong hands-on experience with Microsoft Fabric.
- Advanced SQL/T-SQL skills.
- Strong Python and PySpark experience.
- Strong knowledge of Lakehouse, Warehouse, OneLake, Delta Lake, and Medallion Architecture.
- Strong Power BI, DAX, semantic modeling, and Power Query skills.
- Experience with Direct Lake and Power BI performance optimization.
- Experience with Data Factory and Dataflows Gen2.
- Strong understanding of data modeling and performance tuning.
- Experience with Git, CI/CD, and deployment pipelines.
- Understanding of data security, governance, and monitoring.
- Hands-on experience building Microsoft Fabric Data Agents.
- Experience with Copilot, Azure OpenAI, MLflow, or MLOps.
- Knowledge of Microsoft Purview.
- Experience with Real-Time Intelligence, Eventstreams, Eventhouse, or KQL.
- Experience with Azure SQL, Snowflake, S3, or other external data sources.
- Microsoft Fabric/Azure Data Engineering certification.
Education
- Bachelors degree in Computer Science, Information Technology, Data Engineering, or a related field.
- Thanks & Regards
- Sulabh Tailang
- HR-Talent Acquisition Manager |Celebal Technologies |
- Sulabh.tailang@celebaltech.com|LinkedIn-sulabhtailang
- Website-www.celebaltech.com
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Job application FAQ
Last updated 14 October 2026
- How do I apply for Data Engineer With MS Fabric at Celebal Technologies?
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- What skills matter for this Data Engineer With MS Fabric role at Celebal Technologies?
- This is a mid-level Data Engineer With MS Fabric role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.