Postscript is seeking a Staff Data Engineer to modernize its data stack and build a lakehouse to enable broad data access for BI, Machine Learning, and Engineering teams, ultimately supporting the company's mission to make SMS the number-one revenue channel for ecommerce merchants.
Requirements
- 8+ years as a Data Engineer working on the modern data stack
- 5+ years of experience writing production grade Python code
- You have familiarity with the JVM and at least one JVM language (Java/Scala/Kotlin)
- You’ve worked in modern datalakes with open table formats such as Iceberg, Hudi, or Delta Lake
- You’ve built and operated stream processing pipelines with Apache Flink and/or Spark
- You have strong cloud architecture skills in the AWS ecosystem
- You’ve worked with a broad array of database technologies and understand how to select the right technology for the job (Postgres/OLAP/NoSQL/etc.)
Responsibilities
- Own and evolve our data platform, tooling, and architecture to meet growing analytical and product needs.
- Help dead the delivery of a v2 data architecture at Postscript via a data lakehouse
- Build stream and batch data ingestion pipelines to process source data
- Partner with Engineering, Product, and BI to support net new analytics use cases and migrations
- Support existing data engineering systems
- Mentor and coach other data engineers and backend software engineers in the data practice
Other
- Passionate about data engineering and have strong software engineering skills
- You’re seasoned in event-driven distributed systems
- You have a track record of success at remote mid/late-stage startups
- You’re able to build strong cross-team partnerships and have strong communication + project management skills
