Data Airflow Professional

Mandatory Skills AWS Data Services, Airflow, Podman/Docker containers, GIT, Python, SQLSecondary Skills DBT, Release management, DevOps CI.CDWe are seeking a skilled Data Engineer proficient in Airflow, with expertise in DBT (Data Build Tool). The ideal candidate will play a key role in designing, developing, and maintaining data pipelines, ensuring the reliability and efficiency of data workflows within our organization.ResponsibilitiesOverall 4+ yrs experience with various data platforms, data warehousing initiatives including at least 1 implementation experience in building data pipelines, Schedule, Orchestrate with Airflow and DBT is Mandatory.Having Data Engineering, Orchestration experience using Apache Airflow and Python.Familiarity with containerization and orchestration tools like Podman, Rancher and Kubernetes.Proficient in SQL and Python is a Must.Collaborating with the team for ensuring suitable translation of architectural solutions into robust and effective implementation.Thorough understanding and application of AWS services related to Cloud data platform is mandatory AWS S3, AWS Glue, Amazon Redshift.Stay current with industry trends and advancements in ETL technologies, incorporating new tools and techniques as appropriate like Airflow and DBT specific CICD, Version Control and Automated Testing.Collaborate with infrastructure and DevOps teams to deploy and monitor data pipelines in production environments.Work closely with DBT Engineers to understand the dbt modelsShould have Ability to integrate logically different tasks into Data pipelines.Must have good exposure to configure, schedule and orchestrate pipelines.

Qualification

Mandatory Skills AWS Data Services, Airflow, Podman/Docker containers, GIT, Python, SQLSecondary Skills DBT, Release management, DevOps CI.CDWe are seeking a skilled Data Engineer proficient in Airflow, with expertise in DBT (Data Build Tool). The ideal candidate will play a key role in designing, developing, and maintaining data pipelines, ensuring the reliability and efficiency of data workflows within our organization.ResponsibilitiesOverall 4+ yrs experience with various data platforms, data warehousing initiatives including at least 1 implementation experience in building data pipelines, Schedule, Orchestrate with Airflow and DBT is Mandatory.Having Data Engineering, Orchestration experience using Apache Airflow and Python.Familiarity with containerization and orchestration tools like Podman, Rancher and Kubernetes.Proficient in SQL and Python is a Must.Collaborating with the team for ensuring suitable translation of architectural solutions into robust and effective implementation.Thorough understanding and application of AWS services related to Cloud data platform is mandatory AWS S3, AWS Glue, Amazon Redshift.Stay current with industry trends and advancements in ETL technologies, incorporating new tools and techniques as appropriate like Airflow and DBT specific CICD, Version Control and Automated Testing.Collaborate with infrastructure and DevOps teams to deploy and monitor data pipelines in production environments.Work closely with DBT Engineers to understand the dbt modelsShould have Ability to integrate logically different tasks into Data pipelines.Must have good exposure to configure, schedule and orchestrate pipelines.