As a Data Engineer, your role will encompass: 

• Designing and building production data pipelines from ingestion to consumption within a hybrid big data architecture using Scala, Python, Talend etc.   
• Gather and address technical and design requirements.  
• Refactor existing applications to optimize its performance through setting the appropriate architecture and integrating the best practices and standards. 
• Participate in the entire data life-cycle mainly focusing on coding, debugging, and testing. 

• Troubleshoot and debug ETL Pipelines. 
• Documentation of each process. 

Technical Requirements: - 

• BSc degree in Computer Science/Computer Engineering. (Masters is a plus.) 
• 2+ years of experience as a Data Engineer. 

• In-depth understanding of core ETL concepts, Data Modelling, Data Lineage, Data Governance, Data Catalog, etc. 
• 2+ years of work experience in Scala, Python, Java. 
• Good Knowledge on Big Data Tools such as Spark/HDFS/Hive/Flume, etc. 
• Hands on experience on ETL tools like Talend/Informatica is a plus. 
• Good knowledge in Kafka and spark streaming is a big plus. 

• 2+ years of experience in using Azure cloud and its resources/services (like Azure Data factory, Azure Databricks, SQL Synapse, Azure Devops, Logic Apps, Power Bi, Azure Event Hubs, etc). 
• Strong experience in Relational Databases (MySQL, SQL Server)  
• Exposure on data visualization tools like Power BI / Qlik sense / MicroStrategy 
• 2+ years of experience in developing APIs (REST & SOAP protocols). 
• Strong knowledge in Continuous Integration & Continuous Deployment (CI/CD) utilizing Docker containers, Jenkins, etc. 

• Strong competencies in algorithms and software architecture. 
• Excellent analytical and teamwork skills. 

 Good to have: - 

• Previous on-prem working experience is a plus. 
• In-depth understanding of the entire web development process (design, development, and deployment) 

• Previous experience in automated testing including unit testing & UI testing.