Improve our Data Engineering stack through containerization, data modeling, developing our ETL pipelines, and more.
Use your expertise in data modeling to design, build, and maintain our analytics data warehouse, which provides clean, accurate, and robust data sets that can be leveraged for reporting, analytics, and machine learning initiatives.
Work with stakeholders and translate their needs and expectations into action items and deliverables.
Continue to learn more about the Data Engineering discipline, utilize that knowledge in your deliverables, and identify opportunities to enhance our pipelines.
- Participate in our on-call rotation to ensure system reliability, promptly addressing issues to ensure smooth operations.
- What We're Looking For:
- 5+ years of professional/industry experience
Proficient in Python, SQL, DevOps, and databases.
5+ years of professional/industry experience.
Experience delivering data products from conception to delivery and with the infrastructure that supports their underlying processes.
Experience modeling data sets for different types of sources and business processes.
Passionate about designing elegant data infrastructure, tooling, and pipelines.
Familiarity with our stack: Kubernetes, Docker, Terraform, Kafka, Airflow, dbt, Looker, AWS technologies (S3, Redshift), GCP technologies (Dataflow, BigQuery). and CI/CD technologies (CircleCI), Spark, Databricks
