About the role


We’re looking for engineers with a keen eye for detail and a healthy impatience for mediocrity. Trellis is a cloud-native company and we’re serious about doing infrastructure the right way.


Data is a core part of our infrastructure, and one of our highest levers for growth. We are constantly expanding our data schema to extract more pertinent financial information from our third party sources. We need technical expertise to keep our data platform humming.


In this role, expect to



  • Manage the configuration, deployment, and maintenance of our data pipeline.

  • Unlock the product engineering team from constant ETL maintenance.

  • Empower our analytics team with modern data infrastructure tools.

  • Identify opportunities to incorporate new technologies or techniques into our process that improve data reliability and consistency.


To succeed in this role, you have



  • Several years of experience as a data engineer.

  • At least two years of experience with data warehousing applications utilizing tools like BigQuery, Hadoop, Amazon Redshift, Google Spanner, Apache Hive

  • Experience with real-time streaming applications such as Amazon Kinesis, Apache Kafka, or Apache Spark

  • A high comfort level with data orchestration and transformation systems like Airflow and DBT.

  • A “reliability” mindset, bare curious and diligent in discovering ways to improve reliability

  • Excellent knowledge of data backup, recovery, security, integrity and SQL

  • Work quickly and efficiently with a good sense of prioritization.


Nice to have, but not essential



  • Familiarity with a BI Platform like Looker or Tableau

  • Familiarity with database design, documentation, and coding

  • Familiarity with Terraform, Ansible or similar infrastructure management tools

  • Experience working in highly distributed container-based systems (Kubernetes, ECS)

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