Remote Data Engineer: Production Pipelines & Analytics

Remote; San Francisco (CA); Remote; USD 115,000 - 140,000; Full time

Benefits offered by this job

Remote first work environment

Health, Dental, Vision, Life and DI

401K - with match

17 company holidays, 2 floating days

Internal Advancement Opportunities

Job summary

PerfectServe is building a data platform to ingest, transform, and model data from across our product portfolio. You’ll work closely with staff data engineers and platform engineers, owning production pipelines and contributing to design reviews.

Join a small, dedicated team in a remote-first environment, with the opportunity to deploy to production and learn quickly while shaping data practices across the company.

Qualifications

• Experience building data pipelines with production ownership.
• Strong SQL and one programming language (Python or Go).
• Hands-on dbt or another transformation framework.
• Experience with a cloud data warehouse (Snowflake/BigQuery/Redshift).
• Experience with ELT and orchestration tools (Fivetran, Airflow).
• Working knowledge of AWS and data testing practices.

Responsibilities

• Build and maintain ingestion pipelines from production source systems.
• Write transformation models turning raw data into trusted datasets.
• Apply dimensional and medallion modeling patterns as the warehouse evolves.
• Deploy pipelines to production and perform data quality checks and idempotent tests.
• Contribute to data model and schema design and participate in design reviews.
• Document pipelines and create runbooks for maintenance and handover.

Skills

SQL

Python

Go

dbt

Data modeling

ELT tooling

AWS

Data testing

Tools

Snowflake

BigQuery

Redshift

Fivetran

Airflow

Job description

PerfectServe is building a data platform to ingest, transform, and model data from across our product portfolio. You’ll work closely with staff data engineers and platform engineers, owning production pipelines and contributing to design reviews.

Join a small, dedicated team in a remote-first environment, with the opportunity to deploy to production and learn quickly while shaping data practices across the company.