Job
Description
Job Title: Data Engineer Location: Bangalore, Karnataka Experience: 6 to 9 years Salary: 17.50 LPA Employment Type: Full-time Skills: Data modeling, SQL, Snowflake, Python, AWS, NOSQL Good to have NO SQL data modelling Job Summary: As a Data Engineer, you will design, develop, and manage data pipelines that support analytics and business intelligence (BI) initiatives. You will be responsible for ensuring data quality, efficiency, and scalability in a cloud-native environment. You will collaborate with cross-functional teams including Data Scientists, BI Analysts, and Software Engineers to optimize data flows and implement effective data solutions. Our team is growing, and we are looking for a Data Engineer with experience in SQL, Snowflake, Python, AWS, and NoSQL databases to help us scale our data infrastructure and support business intelligence initiatives. Key Responsibilities: Design and implement efficient, scalable data models in Snowflake and other cloud data platforms. Build, maintain, and optimize data pipelines to support data ingestion, transformation, and storage. Develop and manage ETL processes using Python, SQL, and Snowflake. Collaborate with stakeholders to identify data requirements and create data solutions. Work with NoSQL and SQL databases (such as MongoDB, Cassandra, PostgreSQL) for handling diverse data types. Deploy and manage data workflows on AWS, utilizing services such as S3, Redshift, and Lambda. Perform data validation and ensure data integrity, consistency, and accuracy. Assist in troubleshooting and resolving data-related issues. Provide insights and recommendations for process optimization and automation. Skills and Qualifications: 6 to 9 years of experience in Data Engineering or similar roles. Strong hands-on experience with Snowflake, SQL, Python, and AWS services (Redshift, S3, Lambda). Expertise in designing data models for both structured and unstructured data. Experience with NoSQL databases (MongoDB, Cassandra, etc.) is a plus. Strong knowledge of data warehousing concepts and data integration patterns. Hands-on experience in building scalable data pipelines using ETL frameworks. Proficiency in data pipeline orchestration tools like Airflow is a plus. Strong problem-solving skills and the ability to work independently and as part of a team. Good communication skills to work with cross-functional teams.
