Senior Data Engineer—ML & Personalization Platform

Cricut; South Jordan (UT); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

401(k) match

Generous PTO

Tuition reimbursement

Lifestyle stipend

Employee discounts

Job summary

Cricut is seeking a Senior Data Engineer to shape the data foundation behind product analytics, personalization, and AI initiatives. You’ll own the event data platform from instrumented apps to warehouse, building pipelines and feature infrastructure for recommendations and learning models.

You’ll collaborate with product engineering, data science, ML engineering, analytics, and experimentation teams to ensure reliable, well‑modeled data for decision making and production ML workflows.

Qualifications

• 8+ years building and owning production data pipelines at scale.
• Strong SQL and Python; PySpark or Spark a plus.
• Hands‑on AWS data services experience (S3, Glue, Redshift, DynamoDB).
• Production Airflow/DAG design, dependencies, backfills, alerting.
• Experience with streaming and event ingestion (Kafka, Kinesis, SQS).
• Data modeling expertise and understanding impact on metrics.
• Proven data quality and observability frameworks.
• Experience supporting ML systems in production and feature pipelines.
• Ability to write clear design docs and lead cross‑functional work.
• Excellent communication with engineers, data scientists, and partners.

Responsibilities

• Design, build, and operate scalable batch and streaming pipelines on AWS using Airflow, Glue, Kafka, S3, and Redshift.
• Lead evolution of product event platform with schema design, taxonomy, and migrations.
• Build data quality, observability, and lineage across pipelines.
• Handle late arrivals with lookback reprocessing and idempotent loads.
• Maintain foundations for personalization and recommendation datasets for models.
• Partner with ML engineers to build feature pipelines and a feature store for real-time serving.
• Support ML workflows on AWS Batch and SageMaker, including training data delivery.
• Instrument data for AI-powered experiences and model improvement feedback loops.
• Develop fact and dimension models powering BI and exploration platforms.
• Tune warehouse performance and cost; set code review, testing, CI/CD standards, and mentor others.

Skills

SQL

Python

PySpark

Airflow

AWS

Kafka

Redshift

DynamoDB

S3

Data Modeling

Tools

Glue

Lambda

IAM

Kinesis

Apache Airflow

Job description

Cricut is seeking a Senior Data Engineer to shape the data foundation behind product analytics, personalization, and AI initiatives. You’ll own the event data platform from instrumented apps to warehouse, building pipelines and feature infrastructure for recommendations and learning models.

You’ll collaborate with product engineering, data science, ML engineering, analytics, and experimentation teams to ensure reliable, well‑modeled data for decision making and production ML workflows.