Staff Data Platform Engineer

Teleport; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Extensive health coverage

Annual expense budget

Rest and recovery policies

Retirement savings plans

Professional development opportunities

Job summary

Teleport is hiring its first Data Engineer to build the internal data platform. You will own pipelines and the warehouse that turn raw data from product usage, costs, budgets, and sales into usable data for all teams.

You will partner across product, engineering, finance, and revenue to deliver reliable, well-modeled data that teams can depend on. You’ll design data models, pipelines, and data quality checks, while handling sensitive data with proper access control and retention practices.

Qualifications

• Experience designing and building data pipelines feeding a central data warehouse.
• Strong SQL and data modeling skills with well-documented schemas.

Responsibilities

• Design and build data pipelines ingesting data from internal sources into a central warehouse.
• Create performant, well-documented data models and schemas that evolve with business needs.
• Implement data quality checks and validation to prevent bad data.
• Enforce data access controls, retention policies, and handling of sensitive data.
• Collaborate with product, engineering, finance, and revenue teams to scope new data sources and enable self-serve access.

Skills

Data modeling

SQL

Collaboration

Builder mentality

Data governance

Security awareness

Willingness to learn

Adaptability

Attention to detail

Tools

Snowflake

BigQuery

Redshift

Python

Go

Airflow

dbt

Job description

Teleport is hiring its first Data Engineer to build the internal data platform. You will own pipelines and the warehouse that turn raw data from product usage, costs, budgets, and sales into usable data for all teams.

You will partner across product, engineering, finance, and revenue to deliver reliable, well-modeled data that teams can depend on. You’ll design data models, pipelines, and data quality checks, while handling sensitive data with proper access control and retention practices.