All fields marked * are required
Job Description – Azure Data Engineer
Experience: 6-12+ Years
Work Mode: Work from Office – 5 Days a Week
Shift: 12:30 PM – 9:30 PM IST
We are looking for an experienced Azure Data Engineer with strong expertise in Azure, Azure Data Factory (ADF), Databricks, PySpark/Python, SQL, Data Warehousing, and ETL. The ideal candidate should be capable of designing and implementing scalable data solutions, working with large datasets, preparing source-to-target mappings, and mentoring junior team members.
Design and implement scalable data ingestion, transformation, and ETL pipelines using Azure technologies.
Develop and maintain data pipelines using Azure Data Factory (ADF).
Work extensively with Azure Databricks and PySpark/Python for data processing and transformation.
Develop complex SQL queries and work with data warehouse solutions.
Understand business requirements and create Source-to-Target Mapping (STTM) and technical specification documents.
Design and implement data warehouse solutions based on business and technical requirements.
Perform data integration from multiple sources into cloud-based data platforms.
Ensure data quality, reliability, scalability, and performance of data pipelines.
Troubleshoot data pipeline and production issues and provide effective solutions.
Collaborate with technical and business stakeholders to understand requirements and deliver data solutions.
Mentor and guide junior team members on technical implementation and best practices.
Be flexible to work from client office locations as required.
6+ years of experience in Data Warehousing and ETL.
Strong hands-on experience with Microsoft Azure data technologies.
Strong experience with Azure Data Factory (ADF).
Hands-on experience with Azure Databricks.
Strong PySpark/Python programming experience.
Strong SQL skills.
Good understanding of Data Warehouse concepts, ETL processes, data modelling, and data integration.
Experience creating and understanding Source-to-Target Mapping (STTM).
Ability to create technical/design specification documents.
Strong problem-solving and communication skills.
Relevant Azure/Databricks or other cloud certifications.
Experience in the Banking/Financial Services domain.
Exposure to Risk & Regulatory, Commercial Banking, or Credit Cards/Retail Banking.
Experience working in client-facing environments.
Experience mentoring junior data engineering resources.
The ideal candidate should be a hands-on senior data professional who combines strong Azure Data Engineering expertise with solid Data Warehouse and ETL fundamentals. The candidate should be comfortable taking ownership of technical solutions, interacting with stakeholders, and guiding junior team members.
Required
Preferred
All fields marked * are required
Job Description – Azure Data Engineer
Experience: 6-12+ Years
Work Mode: Work from Office – 5 Days a Week
Shift: 12:30 PM – 9:30 PM IST
We are looking for an experienced Azure Data Engineer with strong expertise in Azure, Azure Data Factory (ADF), Databricks, PySpark/Python, SQL, Data Warehousing, and ETL. The ideal candidate should be capable of designing and implementing scalable data solutions, working with large datasets, preparing source-to-target mappings, and mentoring junior team members.
Design and implement scalable data ingestion, transformation, and ETL pipelines using Azure technologies.
Develop and maintain data pipelines using Azure Data Factory (ADF).
Work extensively with Azure Databricks and PySpark/Python for data processing and transformation.
Develop complex SQL queries and work with data warehouse solutions.
Understand business requirements and create Source-to-Target Mapping (STTM) and technical specification documents.
Design and implement data warehouse solutions based on business and technical requirements.
Perform data integration from multiple sources into cloud-based data platforms.
Ensure data quality, reliability, scalability, and performance of data pipelines.
Troubleshoot data pipeline and production issues and provide effective solutions.
Collaborate with technical and business stakeholders to understand requirements and deliver data solutions.
Mentor and guide junior team members on technical implementation and best practices.
Be flexible to work from client office locations as required.
6+ years of experience in Data Warehousing and ETL.
Strong hands-on experience with Microsoft Azure data technologies.
Strong experience with Azure Data Factory (ADF).
Hands-on experience with Azure Databricks.
Strong PySpark/Python programming experience.
Strong SQL skills.
Good understanding of Data Warehouse concepts, ETL processes, data modelling, and data integration.
Experience creating and understanding Source-to-Target Mapping (STTM).
Ability to create technical/design specification documents.
Strong problem-solving and communication skills.
Relevant Azure/Databricks or other cloud certifications.
Experience in the Banking/Financial Services domain.
Exposure to Risk & Regulatory, Commercial Banking, or Credit Cards/Retail Banking.
Experience working in client-facing environments.
Experience mentoring junior data engineering resources.
The ideal candidate should be a hands-on senior data professional who combines strong Azure Data Engineering expertise with solid Data Warehouse and ETL fundamentals. The candidate should be comfortable taking ownership of technical solutions, interacting with stakeholders, and guiding junior team members.
Required
Preferred