Data Engineer

Job description Requirements - Implement/support new data solutions in datalake/datawarehouse built on snowflake. - Develop and design data pipelines using python, spark and snowflake. - Implement infrastructure as code using cloudformation and terraform. - Design and Implement Continuous Integration/Continuous Deployments pipelines. - Perform Data Modelling using downstream requirements. - Develop transformation scripts using advanced SQL and DBT. - Create reports/dashboard using business intelligence tools such as looker and tableau. - Write test cases/scenarios to ensure incident free production release. - Collaborate closely with data analysts and different domains such as Finance, risk, compliance, product and engineering to fulfil requirements. - Identify areas of improvements in data pipelines, snowflake, infrastructure etc Conduct peer reviews of the code. - Debug production and development issues and provide support to colleagues where necessary. - Perform data quality checks to ensure quality of the data exposed to the end users. - Perform production deployments and perform a post-production support and validation (We follow a 'You build, you run it' philosophy) - Build strong relationships with team, peers and stakeholders. - Contributes to overall data platform implementation. - Proficient in SQL/Python/Spark - Exposure to DBT would be preferable - Experience in AWS services such as Glue, Lambda, S3, DynamoDB, RDS, Kinesis, ECS/Fargate. - Experience working with modern data platforms such as redshift or snowflake - Experience working with BI tools such as looker and tableau - Experience working with docker - Proficient in data modelling. Skills: Gcp, Sql, Aws, Python Experience: 4.00-9.00 Years