Design and scale our data platform including pipelines, models, and orchestration frameworks
Develop scalable ETL/ELT pipelines for ingesting data from APIs, databases, and event streams
Define and implement systems for data ingestion, storage, processing, and transformation
Build and manage workflow orchestration using tools like Airflow
Build semantic layer as well as dashboards
Establish best practices for data modeling, testing, and quality
Partner with stakeholders to shape data requirements and enable BI and analytics use cases
Optimize systems for performance, scalability, and cost from day one and apply software engineering principles (testing, CI/CD, modular design) to data infrastructure

Requirements

A min of 5+ years of software engineering experience with the last 2-3 years in data engineering, ideally including early-stage or 0→1 environments
Strong programming skills in Python
Advanced proficiency in SQL
Proven experience building ETL/ELT pipelines end-to-end
Experience with orchestration tools like Airflow
Deep understanding of the data lifecycle: ingestion → storage → processing → transformation → serving
Experience with cloud platforms (AWS, GCP, or Azure)
Familiarity with modern data warehouses (Snowflake, BigQuery, Redshift) and experience supporting BI tools (Looker, Tableau, etc.)

Benefits

100% covered health, dental, and vision insurance for employees (50% for dependents)
Generous PTO, including parental leave
401(k)
Company laptop and home-office stipend
Bi-Annual Company retreats for in-person collaboration

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonSQLETLELTdata modelingdata processingdata transformationworkflow orchestrationCI/CDmodular design

Soft Skills

collaborationstakeholder engagementproblem-solvingcommunicationbest practices establishment