Design, build, and maintain scalable and resilient data pipelines using Spark, Presto, and SQL
Develop high-quality ETL workflows to ingest, transform, and aggregate data from multiple upstream sources
Partner closely with data analysts, finance partners, and product teams to understand business needs
Design and evolve data models that accurately represent financial entities and member behavior
Champion data quality by implementing checks, validations, and monitoring
Monitor, troubleshoot, and optimize data workflows for performance and maintainability
Contribute to improving data engineering best practices, tooling, and documentation

Requirements

3–4+ years of experience building and maintaining data pipelines in a production environment
Hands-on experience with distributed data processing technologies such as Spark and query engines like Presto
Strong proficiency in at least one major programming language (e.g. Java, Scala, Python)
Solid understanding of ETL design, data modeling, and data architecture fundamentals
Strong data intuition with a focus on usability and correctness
Ability to collaborate effectively with cross-functional partners and communicate technical concepts clearly
A mindset of ownership, curiosity, and continuous learning.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

SparkPrestoSQLETLdata modelingdata architectureJavaScalaPythondata processing

collaborationcommunicationownershipcuriositycontinuous learningdata intuitionusability focuscorrectness focus