Data Engineer
Entry-level Data Engineer building and maintaining data pipelines on a medallion lakehouse architecture using Python and SQL. Works under guidance on ingestion, transformation, orchestration, and monitoring tasks.
Pipeline & Data Tasks
- Develop and execute well-defined data engineering tasks — creating and modifying data models, writing ingestion scripts, and updating transformations following engineering standards
- Orchestrate data flow through PrizePicks' medallion lakehouse architecture: Landing-Bronze-Silver-Gold
- Deploy, execute, and monitor data jobs and workflows, respond to failures following established runbooks during oncall
Code Quality & Development
- Author robust Python and SQL code following team conventions, with guidance on style, structure, and testing
- Adhere to team standards for model organization, naming, and documentation
- Conduct code reviews - give and receive feedback constructively
- Implement unit tests and adopt what good test coverage looks like for data pipelines
Collaboration & Ownership
- Own assigned pipeline tasks - follow through, communicate blockers early, and see work to completion
- Collaborate actively in agile rituals and team discussions
- Document technical builds: models, runbooks, and decisions. Share learnings with the team.
- Partner with Analytics, MLE, and Product stakeholders to understand how the data you produce gets used and find opportunities to better serve stakeholders.
Requirements
- A bachelor's degree in Computer Science, Mathematics, or a related quantitative field, or equivalent hands-on experience
- Good knowledge of Python - you can write a script, work with data structures, and follow a coding style guide
- Experience working with cloud environments (GCP, AWS, Azure)
- Familiarity with SQL - you can write queries, understand joins, and read a schema
- Familiarity with data engineering concepts: ETL/ELT, APIs, data pipelines, or similar
- Curiosity about how data moves through systems and a desire to understand the full stack
- Clear written and verbal communication skills - you can explain what you're working on and flag when you're stuck
- Ownership mindset: takes responsibility for assigned tasks and follows through reliably
Nice-to-Haves
- Exposure to GCP
- Familiarity with a workflow orchestration tool (Airflow, Argo, etc.)
- Experience with Big Query, dbt, Spark, Kafka, or Iceberg
- Experience with containerization or Kubernetes
- Experience with Infrastructure as Code tooling (Terraform, CrossPlane)
Compensation & Benefits
- Typical salary range: $105,000 to $140,000
- Company-subsidized medical, dental, & vision plans
- 401(k) plan with company match
- Annual bonus
- Flexible PTO (2 weeks strongly encouraged)
- Generous paid leave programs, including 16-week paid parental leave and disability benefits
- Workplace flexibility and modern work schedules
- Company-wide in-person events and team outings
- Lifestyle enhancement program
- Company equipment provided (Windows & Mac options)
- Annual performance reviews with opportunities for growth and career development
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