Anduril · boards.greenhouse.io · checked today
Data Platform Lead, Product Lifecycle Operations
Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold.
Skills, with evidence
- Python
Direct coding experience, using Python, SQL, React, TypeScript, or similar.
must have - SQL
Direct coding experience, using Python, SQL, React, TypeScript, or similar.
must have - Dashboards & BI
Build custom dashboards and analytical tools.
must have · not practised here - Data quality
drive systematic data integrity.
must have - Data modelling
Transform raw data into actionable insights for product teams and executive leadership alike.
must have - AWS
Deep understanding of data stack tools like Palantir Foundry or Databricks.
not practised here - Cost & performance
Start by being scrappy to deliver quickly, collect stakeholder feedback across multiple cycles, then formalize and optimize over time.
- Spark
Deep understanding of data stack tools like Palantir Foundry or Databricks.
- Governance & security
Use of this provider helps to ensure compliance with applicable laws and protect technology, intellectual property, and organizational security.
not practised here
Your plan
- The SQL screen: correct, then fast≈ 2 h
SQL · Data quality
- Airbnb: converting on a day with no published rateAdvanced
- Amazon: net revenue across two fan-outsAdvanced
- Build a percentile tableAdvanced
- Duplicate snapshot keysAdvanced
- Flag outlier ordersAdvanced
- Python: the data-wrangling round≈ 4 h
Python
- Data modelling: the round most people fail≈ 4 h
Data modelling
- Spark: read the plan Spark actually ran≈ 2 h
Cost & performance · Spark
- applyInPandas per country: what Spark ships to Python, and the native rewriteAdvanced
- Filters you wrote in the wrong place: where Catalyst moves themAdvanced
- snappy, gzip or zstd: measure the Parquet codec trade-off yourselfAdvanced
- A correlated COUNT(*) subquery: the join Spark runs, and the count bug it avoidsAdvanced
- Find the four suspects in a slow pipeline (one of them is innocent)Advanced
- Say it out loud≈ 1 h
20 drills · Advanced + Intermediate≈ 12 hours
Not covered by the plan: Dashboards & BI, AWS, Governance & security.
Readiness
Counted from drills you have completed anywhere on D8LooP.
leaves in 13 dremoved the moment Anduril closes it