Data Engineer

• Implementing ingestion pipelines, using Airflow as the orchestration platform, for consuming data from a wide variety of sources (API, SFTP, Cloud Storage Bucket, etc.).
• Implementing transformation pipelines using software engineering best practices and tools (DBT)
• Working closely with Software Engineering and DevOps to maintain reproducible infrastructure and data that serves both API-only customers and in-house SaaS products
• Defining and implementing data ingestion/transformation quality control processes using established frameworks (Pytest, DBT)
• Building pipelines that use multiple technologies and cloud environments (for example, an Airflow pipeline pulling a file from an S3 bucket and loading the data into BigQuery)
• Create and ensure data automation stability with associated monitoring tools.
• Review existing and proposed infrastructure for architectural enhancements that follow both software engineering and data analytics best practices.
• Working closely with Data Science and facilitating advanced data analysis (like Machine Learning)

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