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ELT (Bigquery, dbt, Airflow, Kafka) You will be primarily developing and maintaining processes and solutions in our data platform using technologies such as GCP, AWS, Airflow, Terraform, BigQuery, Kafka, Kubernetes, Snowflake, Python.
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Experience with workflow orchestration management engines such as Airflow, Dagster, DBT, etc. Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc.
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First hand knowledge of the latest ETL/ELT tooling and vendors (dbt, Airflow, Prefect, Fivetran, Segment, Stitch, etc. Design and implementation experience with at least one of the major Cloud Data Warehouses (Snowflake, BigQuery, Redshift, etc.
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Build and maintain big data ETL pipelines using DBT and Airflow. Demonstrated understanding of Airflow and Google Composer. Build and maintain big data ETL pipelines using DBT and Airflow.
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Experience with data orchestration technologies using DAG frameworks (e.g. Airflow, etc.) Deep technical expertise in designing data models in dbt (or other data transformation tools) and implementing them as high-quality core data assets leveraged across the company.
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Familiarity with modern data stack components including data ingestion (e.g. Fivetran, Airbyte), transformation (e.g. DBT), and orchestration (e.g. Airflow, Dagster). Data Pipeline Skills: Proven ability in designing and operating high-velocity data pipelines, with proficiency in tools like Apache Airflow and Benthos.
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3+ years of experience with AWS, Snowflake, DBT, and Airflow. Leading the integration of technologies like DBT into our stack, setting guidelines and best practices. Weekly Virtual Bootcamp, Yoga and Mindfulness Meditation sessions.
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Proficiency in Python, PySpark Scala, Java, SQL, Airflow, dbt. Skilled in modern data platforms (Azure Synapse, Databricks, Redshift, Big Query, Snowflake). Proficiency in Python, PySpark Scala, Java, SQL, Airflow, dbt.
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Experience with enterprise workload automation and job scheduling tools such as Control-M, JAMS, CA Workload Automation, Tidal Enterprise Scheduler, Airflow or similar. Leverage technologies and languages such as Hevo, DBT, Python, SQL, Sacala, Bash and more.
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Google Cloud Platform: Vertex AI, AI/Client, Data Proc, Data Flow, Big Query, Pub/Sub, Cloud Logging and Monitoring AI/Client Tools: Seldon Infrastructure as code: Terraform / GitHub ELT Framework: DBT Orchestrator/ Schedule: Astronomer/Airflow Programming Language/ Scripting Python, Shell scripting IDE: VS code Agile Software: Rally.
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Proficient with one or more big data & new data technologies such as DBT, NIFI, Airflow, Kafka. Solid understanding of cloud data services: AWS services such as S3, Athena, EC2, RedShift, EMR, EKS, RDS and Lambda.
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Proficiency in data engineering tools and technologies - SQL, Python, Spark, DBT, Airflow, Kafka. Proficiency in data engineering tools and technologies - SQL, Python, Spark, DBT, Airflow, Kafka.
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General understanding of orchestration best practices and workflow management tools (Airflow, Luigi, etc. Ability to write complex SQL, ad-hoc data pipelines, and data models, preferably in DBT.
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Proficiency in data analysis languages and tools such as SQL, Python, R, Alteryx, and dbt. Proficiency in data engineering and governance languages and tools such as Airflow, SQL, and Alation.
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