• Software development skills (some combination of Python, Java, Scala, Go)
• High proficiency in SQL
• Experience building and maintaining data ingestion pipelines using a workflow orchestration system (e.g. Prefect, Dagster, Airflow)
• Working knowledge of MLOps best practices
• Working knowledge of dbt or similar data transformation tools
• Highly motivated self-starter that is keen to make an impact and is unafraid of tackling large, complicated problems
• Excellent communication skills, able to explain technical topics to non-technical audiences, and maintain many of the essential cross-team and cross-functional relationships necessary for the team’s success

Desirable

• We are looking for a Senior Data Engineer who can help maintain frameworks and systems that acquire, validate/cleanse, and load data into and out of our analytics systems
• The systems that this role builds and maintains will allow our business partners to more accurately and reliably track and forecast sales, revenue, and usage/consumption metrics
• Additionally, this position will lead the development of machine learning pipelines as we move to productionalize internal predictive models
• This position will have engagement across many parts of the company, including finance, revenue and cx operations, analytics teams, and analytic engineering
• The frameworks and systems that you work on will integrate with and enhance our current stack that includes GCP, BigQuery, dbt, Prefect, Python, Fivetran, Rudderstack, Hightouch, and Atlan
• Build and maintain production quality data pipelines between operational systems and BigQuery (ingress and egress)
• Implement data quality and freshness checks and monitoring processes to ensure data accuracy and consistency
• Build and maintain machine learning pipelines to automate model validation and deployment
• Create and maintain comprehensive documentation for data engineering processes, systems, and workflows
• Maintain observability and monitoring of our internal data pipelines
• Troubleshoot and resolve data pipeline issues to ensure downstream data availability
• Contribute to our dbt systems by making sure the source and staging layers align with our standards, are efficient, cost-effective, and highly available