Posted on: 23/09/2026
About the Role :
We are looking for an experienced Azure Data Engineer with 7 - 9 years of hands-on experience in designing, developing, and maintaining scalable data engineering solutions on Microsoft Azure.
Key Responsibilities :
- Design, develop, and maintain scalable data pipelines and data engineering solutions using Microsoft Azure.
- Develop and manage ETL/ELT workflows for structured, semi-structured, and unstructured data.
- Build data ingestion pipelines using Azure Data Factory and other Azure data integration services.
- Develop data transformation and processing solutions using Azure Databricks and Apache Spark.
- Write optimized SQL queries, stored procedures, views, and other database objects.
- Integrate data from various sources including relational databases, APIs, files, cloud platforms, and enterprise applications.
- Design and maintain data lakes and data warehouse solutions on Azure.
- Implement batch and near-real-time data processing pipelines as required.
- Develop reusable frameworks and components for data ingestion, transformation, validation, and monitoring.
- Implement data quality checks, validation rules, reconciliation processes, and error handling mechanisms.
- Optimize data pipelines, Spark jobs, SQL queries, and storage for improved performance and cost efficiency.
- Monitor pipeline execution, troubleshoot failures, and resolve production data issues.
- Implement logging, alerting, monitoring, and operational support mechanisms.
- Work closely with data architects, analysts, application teams, and business stakeholders to understand data requirements.
- Participate in data migration, modernization, and cloud transformation initiatives.
- Implement security controls, access management, encryption, and governance requirements for Azure data platforms.
- Maintain technical documentation for data pipelines, architecture, processes, and operational procedures.
- Follow best practices for coding, version control, testing, deployment, and production support.
Technical Skills :
- 7 - 9 years of experience in data engineering, ETL development, or related data platform roles.
- Strong hands-on experience with Microsoft Azure data services.
- Strong experience with Azure Data Factory (ADF) for data integration and pipeline development.
- Hands-on experience with Azure Databricks and Apache Spark.
- Strong proficiency in SQL and experience working with relational databases.
- Good understanding of Python and/or PySpark for data processing and automation.
- Experience designing and implementing Azure Data Lake-based solutions.
- Knowledge of Azure Synapse Analytics or similar cloud data warehouse technologies.
- Experience working with different data formats such as CSV, JSON, Parquet, and Avro.
- Experience with REST APIs and data ingestion from external systems is preferred.
- Understanding of batch and streaming data processing concepts.
- Experience with Git and version control systems.
- Knowledge of CI/CD practices for data engineering deployments.
- Experience with Azure DevOps or similar deployment and project management tools.
- Understanding of data security, governance, access control, and compliance concepts.
- Knowledge of monitoring and troubleshooting Azure data pipelines.
Preferred Skills :
- Experience with Azure Synapse Analytics.
- Experience with Azure SQL Database.
- Knowledge of Event Hubs, Stream Analytics, or other Azure streaming technologies.
- Experience with Delta Lake and lakehouse architecture.
- Knowledge of data modelling and dimensional modelling concepts.
- Experience with infrastructure automation or Infrastructure as Code.
- Exposure to Terraform or ARM/Bicep templates.
- Experience implementing automated testing for data pipelines.
- Knowledge of performance tuning and cloud cost optimization.
- Exposure to enterprise-scale data migration and modernization projects.
Education :
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Relevant Azure certifications such as Azure Data Engineer Associate will be an advantage.
Key Competencies :
- Strong analytical and problem-solving skills.
- Ability to design scalable and maintainable data solutions.
- Strong understanding of data engineering best practices.
- Good communication and collaboration skills.
- Ability to work independently as well as collaborate with cross-functional teams.
- Strong focus on data quality, reliability, security, and performance.
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Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1673855