Key Responsibilities:

Responsibilities

- Build, maintain and optimize data pipelines for our Enterprise Data Platform using Google Cloud Platform technologies.

- Ingest new data sources from initial discovery & data architecture, through ETL authoring, operationalizing using Dataflow, Airflow (Cloud Composer) DAGs, and post launch lifecycle.

- Research and test current big-data technologies and tools.

- Advanced SQL queries, and modeling.

- Engage vendors with required features to meet business needs.

- Leverage the full value of our vendor integrations and APIs.

- Optimize BigQuery and ETL resources to decrease spend & increase performance.

Minimum Qualifications

- Bachelor s degree in data science, computer science or similar majors with a GPA of at least 3.0 or equivalent experience

- 7+ years of experience in Data Engineering

- 7+ years of experience in at least one OOP language, preferably Python

- Deep SQL knowledge / experience





- Experience in complex pipeline task management (i.e., Airflow and Beam)

- Experience building Data Models

- Experience with Github

Desired Qualifications

- Google Cloud Platform tools or equivalent platform experience using tools s/a BigQuery, Dataflow / Apache Beam, Cloud Composer / Airflow, Pub/Sub, Apache Spark

- Experience using DBT

- Experience with Scalr/Terraform

- Experience with CI/CD

- Experience with marketing technologies like a CDP (Customer Data Platform) and SFMC (Saleforce Marketing Cloud)

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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