Senior Software Engineer (Data)

Job DescriptionResponsibilities Design and Development of cloud-based microservices to collect dataDesign and Development of REST API to serve Data as a ServiceDesign and Development of Data Quality framework to enable automated data quality checks across data pipelinesWrite efficient, maintainable, and reusable code in at least one programming language (e.g., Java, Python, GoLang, GoSu, etc).Responsible for developing and maintaining CI/CD pipelinesMaintain and stabilize existing data pipelines and infrastructure to provide timely, quality and accurate dataAnalysis, Performance Improvement, Development, Deployment and Contribute to overall product requirementsPerform code review and develop best coding practicesIndulge in brainstorming sessions to help team gain technical knowledge and grow equallyDefine release process improvements along with management of pipeline changesCollaborate with peer teams and support each other s on deliverablesQualification Bachelor s or Master s degree in Computer Science or equivalent industry technical skills8+ years of professional development experienceProven lead experience and a strong understanding of the Software Development Life Cycle (SDLC) processIn-depth knowledge on strong experience in any one of the Python, Java, GoLang, C, etc programming language and should be an expert in Object Oriented ProgrammingStrong experience in AWS service - Glue, Athena, Iceberg, MWAA(Airflow), EC2, ECS, Lambda, StepFunction, S3, SQS preferred. Experience in other AWS services are added advantageExpertise in both SQL and NoSQL databases. Experience in Postgres, Redshift, MongoDB and DynamoDB are preferredExperience in Linux and Shell scripting preferredExperience in Docker, Kubernetes, or MicroService preferredExperience in Airflow and Jenkins preferredExperience in FAST API, Flask Framework, SQL alchemy are preferredExpertise in version control tools Git, Bitbucket preferredExperience in creating and implementing a strong data quality system that checks data accuracy at every step, backed by thorough monitoring and observability features Job DescriptionResponsibilities Design and Development of cloud-based microservices to collect dataDesign and Development of REST API to serve Data as a ServiceDesign and Development of Data Quality framework to enable automated data quality checks across data pipelinesWrite efficient, maintainable, and reusable code in at least one programming language (e.g., Java, Python, GoLang, GoSu, etc).Responsible for developing and maintaining CI/CD pipelinesMaintain and stabilize existing data pipelines and infrastructure to provide timely, quality and accurate dataAnalysis, Performance Improvement, Development, Deployment and Contribute to overall product requirementsPerform code review and develop best coding practicesIndulge in brainstorming sessions to help team gain technical knowledge and grow equallyDefine release process improvements along with management of pipeline changesCollaborate with peer teams and support each other s on deliverablesQualification Bachelor s or Master s degree in Computer Science or equivalent industry technical skills8+ years of professional development experienceProven lead experience and a strong understanding of the Software Development Life Cycle (SDLC) processIn-depth knowledge on strong experience in any one of the Python, Java, GoLang, C, etc programming language and should be an expert in Object Oriented ProgrammingStrong experience in AWS service - Glue, Athena, Iceberg, MWAA(Airflow), EC2, ECS, Lambda, StepFunction, S3, SQS preferred. Experience in other AWS services are added advantageExpertise in both SQL and NoSQL databases. Experience in Postgres, Redshift, MongoDB and DynamoDB are preferredExperience in Linux and Shell scripting preferredExperience in Docker, Kubernetes, or MicroService preferredExperience in Airflow and Jenkins preferredExperience in FAST API, Flask Framework, SQL alchemy are preferredExpertise in version control tools Git, Bitbucket preferredExperience in creating and implementing a strong data quality system that checks data accuracy at every step, backed by thorough monitoring and observability features