Senior Data Engineer

About the role

You'll be our Senior Data Engineer, reporting to engineering leadership and taking ownership of a data platform that is still in its early stages. This is a high-ownership, build-from-the-foundation seat: you'll shape the architecture, stand up reliable pipelines and trusted data models, and set the engineering standards that let our data scale with the company. If you want real ownership over foundational infrastructure at a profitable, fast-growing company, rather than maintaining someone else's system at a larger one, this is that role.

Responsibilities

• Platform & Architecture
  • Design and scale our data platform across pipelines, models, and orchestration
  • Define and implement systems for data ingestion, storage, processing, and transformation
  • Optimize systems for performance, scalability, and cost from the start
• Pipelines & Engineering Practices
  • Build scalable ETL/ELT pipelines that ingest from APIs, databases, and event streams
  • Apply software engineering principles such as testing, CI/CD, and modular design to data infrastructure
  • Establish best practices for data modeling, testing, and quality
• Data Enablement & Partnership
  • Build the semantic layer and dashboards that make data usable across the company
  • Partner with engineering, product, and business teams to shape data requirements
  • Enable trusted, accessible data for BI and analytics decision-making

Requirements

Required

• 5+ years building production software, with at least 2 to 3 of those focused on data engineering
• Strong programming skills in Python and advanced proficiency in SQL
• Proven experience building ETL/ELT pipelines end to end, from ingestion through serving
• Hands-on experience with a cloud platform (AWS, GCP, or Azure) and a modern data warehouse (Snowflake, BigQuery, or Redshift)

Nice to have

• Experience with workflow orchestration tools like Airflow
• Experience supporting BI tools such as Looker or Tableau, and building semantic layers and dashboards
• Deep fluency across the full data lifecycle: ingestion, storage, processing, transformation, and serving
• Experience in early-stage or 0-to-1 environments
• Experience with streaming pipelines such as Kafka or Kinesis
• Exposure to ML/AI data pipelines, data analytics, or data science concepts
• Familiarity with Ruby and Rails

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

Pay

For US-based candidates, the target salary range for this role is $170,000 – $190,000 USD, plus equity. Final compensation is determined based on experience, skillset, scope of responsibility, interview performance, and geographic location. We’re committed to paying competitively and equitably.