Senior Software Engineer, Data Engineering

Mixpanel•San Francisco, CA

34d

About The Position

As a Data Engineer on the Growth org, you will collaborate with our cross-functional partners in Data Science, Product, and Finance to build and maintain high quality data sources and build software that maximizes the value and efficacy of that data. We are seeking someone who can contribute both to our data and fullstack codebases. The team operates independent of skill set, so your peers with software engineering backgrounds will execute on data engineering work, and you will make contributions on software systems that don’t directly work with our data systems. We expect that you will co-elevate your teammates and they should do the same for you. Your expertise will help the team build a strong data backbone that is resilient to noise and smoothly handles changes in upstream information, and going beyond this to help drive changes in upstream software systems when they make sense.

Requirements

A strong background in both data and software engineering, with at least 2 years of relevant professional experience.
Proficiency with at least one programming language (Python, Java, etc.), as well as SQL
Excellent debugging and technical investigation skills
Excellent technical communication, ideally with experience collaborating in an asynchronous remote environment
Familiarity with rETL tools (eg: Hightouch, Census, Rudderstack)
Experience with modern data storage technologies (eg: BigQuery SQL, Airflow, and DBT or similar)

Nice To Haves

Python and Django ORM experience
Experience maintaining and improving a large DBT project
Product Analytics familiarity
Experience implementing Medallion Architecture
Technical writing skills (either internal or public-facing)
Experience mentoring and growing engineers

Responsibilities

Build and maintain software and data pipelines across our backend and data orchestration systems.
Design and build data architecture spanning a wide range of complex data, balancing ease of interpretability with cost.
Create and maintain foundational datasets to support analytics, modeling, experimentation, and product/business needs.
Collaborate with, teach, and learn from Engineers on the team and across the wider organization.
Work with Finance and Data Science to ensure we are building the right things in ways people can understand.
Participate in team on-call rotation to improve our systems and keep them healthy.
Build valuable testing and alerting to help maintain our data hygiene.
Write internal technical documentation for the systems that you design, build and maintain, as well as fill gaps in existing documentation.