Lead the implementation of a resilient, privacy-first data platform architecture that powers personalization, ethical AI, and accelerates data-driven decisions
Lead the design, infrastructure, and tooling decisions for platform optimization and consolidation efforts, including the deprecation of legacy and redundant tooling such as Appflow, Prefect, Stitch, Redshift, and Looker
Develop AI-ready architecture by creating semantic layers that define and standardize business logic, enabling data for Agentic AI, and spearheading new support for ML, experimentation, and onboarding to experimentation pipelines like Statsig
Mentor other members of the DE and broader data team, particularly around dbt architecture and query performance.
Act as a technical thought leader, shaping the company’s data strategy and influencing cross-functional roadmaps with data-centric solutions

Requirements

6+ years in data engineering, with extensive experience in data platform development, complex data model designing, and data compliance implementation
Production experience writing performant Python and PySpark code on distributed compute (Spark 3+, Delta Lake)
Existing experience with Databricks is preferred or experience with Redshift and/or Snowflake
Demonstrated expertise in architectural patterns for building high-volume ETL pipelines
Experience with data modeling, Medallion architecture, pipeline design, metrics calculation and technical documentation
BA/BS degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Benefits

Applicant Tracking System Keywords

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

Hard Skills & Tools

PythonPySparkSpark 3+Delta LakeETLdata modelingMedallion architecturemetrics calculationdbtdata compliance

Soft Skills

mentoringtechnical thought leadershipcross-functional collaboration