Data Engineer
- Contribute to data engineering initiatives within an experienced data organization
- Explore and analyze connected datasets to identify patterns and develop high-quality data models
- Partner with the data engineering group to refine and optimize transformation workflows
- Design, build and operationalize large-scale data solutions using AWS services and third-party technologies (Spark, EMR, DynamoDB, Redshift, Kinesis, Lambda, Glue, Snowflake)
- Build production data pipelines covering ingestion through consumption using SQL and Python
- Implement data engineering, ingestion and curation functions on AWS using native or custom tooling
- Lead proofs of concept and guide the transition of validated solutions into scalable production environments across engineering, deployment and commercialization
- Collaborate with analytics teams using Looker, QuickSight and Q to provide clean and reliable datasets
- 5+ years of data engineering experience
- Experience with Python for data engineering work involving ETL/ELT pipelines and related components
- Proficiency with SQL, Python and other data-focused languages
- Ability to design scalable solutions, evaluate emerging data technologies and anticipate new trends to address complex challenges
- Strong communication skills in both spoken and written English
- Startup experience
- Familiarity with Snowflake
- Familiarity with AWS
- Experience with DBT, Dagster, Apache Iceberg or Infrastructure as Code
- Knowledge of scalable data lake and streaming patterns
- Bachelor's Degree in Computer Engineering, Computer Science, or equivalent