Senior Data Engineer

How you will make a difference:

• Own the Spark pipelines at the core of our ML platform in Databricks and optimize for scale, performance, and cost
• Determine the best way to handle Iterable’s unique data model, including the intricacies of our customer’s unstructured data
• Design end-to-end machine learning systems, including data acquisition, data cleaning, data models, model training, model serving, and evaluation
• Build and own the batch and real-time feature stores that house our ML models
• Work closely with the Iterable engineering team to improve our machine learning infrastructure and data quality
• Build, evaluate, and integrate new models that add intelligence to our core product  
• Improve our model performance tracking system
• Collaborate cross-team and cross-functionally to build data and AI products

We are looking for people who have:

• Data expertise: You have built and managed highly scalable data processing solutions (e.g. Spark, Flink), data lakes or warehouses (e.g. Databricks, Snowflake), authored queries (SQL), used workflow management (e.g. Airflow), and have experience maintaining the infra that supports these. You’ve tackled problems involving unstructured data in big data systems.
• Experience building and scaling backend systems: You understand how different parts of the system work together, from data model to user interface, and have an understanding of distributed computing. You have a strong understanding of system design, data structures, and algorithms. Extensive experience with Scala or Python, with a preference for Scala competency.
• Understanding of ML Platform Tech Stack: Demonstrated expertise in how data flows to and from a machine learning tech platform. Knowledge of statistics, modern and classic machine learning techniques. 
• Empathetic Communication: You communicate nuanced ideas clearly, whether you're explaining technical decisions in writing or brainstorming in real-time and engage thoughtfully with other perspectives.

Bonus Points

• Experience building and supporting complex and modern end-to-end ML systems, like LLM pipelines
• AWS experience
• Experience in a SaaS environment
• Experience with IaC (Terraform preferred)
• Exposure to marketing technology

Perks & Benefits: 

• Paid parental leave
• Competitive salaries, meaningful equity, & 401(k) plan
• Medical, dental, vision, & life insurance
• Balance Days (additional paid holidays)
• Fertility & Adoption Assistance
• Paid Sabbatical
• Flexible PTO
• Monthly Employee Wellness allowance 
• Monthly Professional Development allowance 
• Pre-tax commuter benefits
• Complete laptop workstation

The US base salary range for this position at the start of employment is $133,500 - $206,000. Within this range, individual pay is determined by specific US work location, as well as additional factors, including job-related skills, experience, relevant education or training, and internal equity considerations.

Please note that the range listed above reflects only base salary. The total compensation package includes variable pay (where applicable), equity, plus a range of benefits, including medical, dental, vision, and financial. In addition, we offer perks such as generous stipends for health & fitness and learning & development, among others.

Iterable is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Iterable does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Iterable also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance and other similar state laws and local ordinances, and its internal policy, Iterable will also consider for employment qualified applicants with arrest and conviction records.