Senior Data Engineer

WHAT YOU’LL DO: Design data pipelines utilizing ETL tools, event driven software, and other streaming software. Design data architecture that is simple and maintainable while enabling Data Analysts, Data Scientists, and stakeholders to efficiently work with data. Partner with both data scientists and engineers to bring our amazing concepts to reality. This requires learning to speak the language of statisticians as well as software engineers. Ensure reliability and quality in data pipelines and enforce data governance, security and protection of our customer information while balancing tech debt. Partner with product and engineering teams to design data models for downstream consumers. Evaluate and champion new engineering tools that help us move faster and scale our team WHAT YOU’LL NEED: You have 5 years of data engineer experience coding in Python and using SQL. Experience working with at least one major Datawarehouse in BigQuery, Snowflake, Databricks Bachelor's degree in technology or data science or a related filed, work experience can be substituted for education You are comfortable with data engineering tools such as Airflow, dbt, AirByte/ Fivetran, Atlassian suite, GitHub, Terraform as well as Kubernetes. You understand standard ETL patterns, modern data warehousing ideas such as data mesh or data vaulting, and data quality practices regarding test driven design and data observability.

You have experience partnering with data analysts, data scientists, and engineering stakeholders. You have a background in data engineering, computer science, software development or another engineering field You can communicate with a team and articulate ideas to both team members and non-technical stakeholders You have a drive to learn and master new technologies and techniques Bachelor's degree or relevant experience can substitute for formal education Technologies You Will Use Python/ Airflow for data pipeline and automation. Airbyte for ETL purpose dbt for data transformation Snowflake/ BigQuery as Data Warehouse AWS, GCP, Terraform, Kubernetes, GitHub and more: we keep adopting new tools as we grow!