4Bell Technology
Data Engineer- Microsoft Fabric(R-2110)
1,000,000.00-1,200,000.00/A
Any Degree
IT (Information Technology)
Contract
Gurgaon/Gurugram,Hyderabad,Pune,Bangalore/Bengaluru,Chennai,Coimbatore,Mumbai,Kolkata,Indore
03-Nov-2026
Data Engineer Apache Spark Scala Python Apache Airflow Databricks Microsoft Fabric SQL Azure Data Lake Storage (ADLS)
Job Description
Key Responsibilities Analyze existing Databricks notebooks, jobs, and Spark workloads and migrate them to Microsoft Fabric.
Design and develop scalable data processing solutions using Apache Spark, Scala, and Python.
Integrate Microsoft Fabric compute workloads with existing ADLS storage architecture.
Upgrade and modernize Apache Airflow orchestration workflows and scheduling frameworks.
Develop automated validation and testing frameworks for migration accuracy and quality assurance.
Create and execute unit tests, regression tests, and reconciliation processes to ensure functional equivalence between Databricks and Fabric workloads.
Build automation scripts for testing, deployment, and operational monitoring.
Optimize performance, scalability, reliability, and cost efficiency of migrated workloads
. Collaborate with architects, data engineers, QA teams, and business stakeholders to ensure successful migration delivery.
Produce technical documentation, migration playbooks, and knowledge transfer materials.
Required Experience
5+ years of Data Engineering experience in enterprise data platforms.
Strong hands-on expertise in Spark and Scala for large-scale data processing.
Experience developing and maintaining Databricks notebooks, jobs, and workflows.
Hands-on experience with Microsoft Fabric Data Engineering and Lakehouse environments.
Experience upgrading and managing Apache Airflow workflows and DAGs.
Strong experience in automated testing frameworks, unit testing, and validation automation.
Experience developing migration utilities, reconciliation scripts, and deployment automation.
Strong understanding of distributed computing, data transformation, and performance tuning.
Experience with Git, CI/CD pipelines, and DevOps practices.
5+ years of Data Engineering experience in enterprise data platforms.
Strong hands-on expertise in Spark and Scala for large-scale data processing.
Experience developing and maintaining Databricks notebooks, jobs, and workflows.
Hands-on experience with Microsoft Fabric Data Engineering and Lakehouse environments.
Experience upgrading and managing Apache Airflow workflows and DAGs.
Strong experience in automated testing frameworks, unit testing, and validation automation.
Experience developing migration utilities, reconciliation scripts, and deployment automation.
Strong understanding of distributed computing, data transformation, and performance tuning.
Experience with Git, CI/CD pipelines, and DevOps practices.