• Partner closely with business stakeholders to understand and translate data warehouse requirements into technical solutions 

• Provide comprehensive support for data warehouse initiatives including requirements gathering, solution design, and implementation 

• Optimize data warehouse performance through query optimization, indexing strategies, and architectural improvements 

• Design, develop, and maintain robust ETL/ELT pipelines using modern data engineering tools  

• Implement real-time and batch data processing solutions to meet business requirements  

• Develop and maintain data models and DataMart solutions for analytics and reporting needs 

• Deploy and maintain ML model infrastructure ensuring scalability and reliability 

Requirements: 

• 3-6 years of experience in Data Engineering 

• Strong expertise in distributed computing and advanced problem-solving/analytical skills 

• Deep understanding of data warehouse design, optimization, and performance tuning 

• Expertise in Python, SQL and NoSQL databases 

• In-depth experience in Could services, preferably AWS (EMR, S3, Redshift, MSK) 

• Expertise in Data engineering tech stack like Spark (PySpark), Airflow, Debezium, Hadoop 

• Experience in data modelling, DataMart development 

• Understanding of ML model deployment and maintenance workflows with feature store architectures and best practices 

• Good to Have - Experience in setting up and working with On-premises Data Engineering tech stack