Data Engineer, Go Platform — Production Data & Analytics

Superhuman; San Francisco (CA); Hybrid; USD 130,000 - 190,000; Full time

Benefits offered by this job

Excellent health care

Disability and life insurance options

401(k) and RRSP matching

Paid parental leave

20 days paid time off

Job summary

Superhuman is hiring a Data Engineer to build production data pipelines and reusable data models supporting Go and analytics. You will work closely with Product, Engineering, and Data Science to measure adoption, engagement, and growth, delivering reliable data for dashboards and decision-making.

You’ll own data pipelines, improve event logging, and ensure data quality with tests and monitoring while collaborating across Data Platform and Go teams in a hybrid environment.

Qualifications

• 2+ years building and operating production data pipelines.
• Proficient in SQL with experience in lakehouse or cloud data warehouse.
• Experience with workflow orchestration tools such as Airflow or Databricks Workflows.
• Knowledge of data modeling and warehouse design for reusable datasets.
• Ability to test, diagnose data issues, and collaborate with product and engineering.

Responsibilities

• Build and maintain production data pipelines in Databricks that process product events and user activity.
• Develop datasets for onboarding, activation, engagement, retention, and conversion.
• Collaborate with Product, Engineering, and Data Science to define metrics and improve event logging.
• Define clear data models and documentation to enable self-service analytics and AI tooling.
• Link Go usage to customer and account data to measure adoption and growth.
• Ensure datasets stay accurate, tested, and monitored; investigate discrepancies and fix root causes.
• Improve pipeline performance, manage compute costs, and maintain clean code practices.

Skills

SQL

Data modeling

Data pipelines

Databricks

Airflow

Tools

Databricks

Snowflake

Airflow

Git

Job description

Superhuman is hiring a Data Engineer to build production data pipelines and reusable data models supporting Go and analytics. You will work closely with Product, Engineering, and Data Science to measure adoption, engagement, and growth, delivering reliable data for dashboards and decision-making.

You’ll own data pipelines, improve event logging, and ensure data quality with tests and monitoring while collaborating across Data Platform and Go teams in a hybrid environment.