Data Engineer

Role Overview: As a Data Engineer for our data modernisation program, you will play a crucial role in translating business requirements into Azure Cloud-based big data solutions. Your responsibilities will include building complex data pipelines, data warehouses, and data lakes using Azure services such as Azure Data Factory, Azure Databricks, and Azure Synapse Analytics. You will collaborate closely with the Data Engineering team and Product Owners to ensure that data strategy and platforms align with the organization's vision. Key Responsibilities: - Develop high-quality big data technology-based solutions on Azure Cloud using Azure Databricks and other services for advanced data processing and analytics tasks, focusing on optimizing performance and scalability. - Analyze current business practices and identify opportunities to leverage Microsoft Azure Data & Analytics Services for future business growth. - Create best practices, reusable code, libraries, patterns, and frameworks for Azure cloud-based data warehousing and data pipelines. - Collaborate with the Azure Data Engineering Manager and Technical Leads to ensure successful execution of plans. - Drive efficiency improvements in data processing and facilitate migrations from on-premises to public cloud platforms. Qualifications Required: - 4 to 5 years of IT experience with a focus on Data and Analytics implementation. - At least 3 years of experience in Data Engineering (Azure) projects, including analysis, development, configuration, and deployment. - Minimum 2 years of hands-on experience in Azure Data Engineering projects. - Proficiency in Python, SQL, Spark SQL, and PySpark. - Expertise in Azure Data Factory, Azure Synapse Analytics, Azure SQL, Azure Data Lake, Databricks, Purview, and Azure App Service. - Strong technical skills in Transact-SQL and relational database technologies. - Familiarity with data governance and security best practices. - Exposure to distributed data processing frameworks such as Spark, Storm, or Flink. - Experience with NoSQL technologies like MongoDB, Cassandra, or HBase. - Knowledge of CI/CD pipelines, containerization, orchestration, and Kubernetes Engine. - Hands-on experience in developing data pipelines using API ingestion and streaming methods. - Previous work experience in a fast-paced Agile environment. Additional Company Details: The initial rounds of the selection process are scheduled for 20th June 2026 in Bangalore. We are looking for a candidate with a strong background in data technologies and a proactive approach to problem-solving. Excellent communication skills, both written and verbal, along with strong organizational and time-management abilities, are essential for this role. Note: Please note that the qualifications include a Bachelor's or Master's degree in Computer Science, Information Systems, or related field, and/or equivalent work experience. Additionally, Azure Certifications related to Design and Development are required, while professional IT accreditation or qualification is desirable. Role Overview: As a Data Engineer for our data modernisation program, you will play a crucial role in translating business requirements into Azure Cloud-based big data solutions. Your responsibilities will include building complex data pipelines, data warehouses, and data lakes using Azure services such as Azure Data Factory, Azure Databricks, and Azure Synapse Analytics. You will collaborate closely with the Data Engineering team and Product Owners to ensure that data strategy and platforms align with the organization's vision. Key Responsibilities: - Develop high-quality big data technology-based solutions on Azure Cloud using Azure Databricks and other services for advanced data processing and analytics tasks, focusing on optimizing performance and scalability. - Analyze current business practices and identify opportunities to leverage Microsoft Azure Data & Analytics Services for future business growth. - Create best practices, reusable code, libraries, patterns, and frameworks for Azure cloud-based data warehousing and data pipelines. - Collaborate with the Azure Data Engineering Manager and Technical Leads to ensure successful execution of plans. - Drive efficiency improvements in data processing and facilitate migrations from on-premises to public cloud platforms. Qualifications Required: - 4 to 5 years of IT experience with a focus on Data and Analytics implementation. - At least 3 years of experience in Data Engineering (Azure) projects, including analysis, development, configuration, and deployment. - Minimum 2 years of hands-on experience in Azure Data Engineering projects. - Proficiency in Python, SQL, Spark SQL, and PySpark. - Expertise in Azure Data Factory, Azure Synapse Analytics, Azure SQL, Azure Data Lake, Databricks, Purview, and Azure App Service. - Strong technical skills in Transact-SQL and relational database technologies. - Familiarity with data governance and security best pr