Data Engineer, Places

The role

Build reliable systems for place and location data including ingestion, quality, attribution, experimentation, and production use. Work with noisy real-world signals and large geospatial datasets.

What you will do

• Build pipelines for place and location-related data
• Work with noisy real-world signals and large geospatial datasets
• Improve quality, reliability, and observability of derived datasets
• Define metrics and feedback loops for data quality and attribution
• Prototype in Python, SQL, notebooks, or similar tools
• Integrate scoped production experiments with amo's backend systems
• Run offline evaluations and A/B tests where relevant

Required qualifications

• Strong Python and SQL
• Production experience with Python or Scala
• Experience with PySpark, Spark SQL, Spark Streaming, Parquet, and Iceberg
• Experience with large datasets and data pipelines
• Experience with geospatial data, POI datasets, place matching, or similar real-world entity data
• Comfort with metrics, experimentation, and data quality measurement
• Comfort working near backend systems and reading production code

Nice to have

• Experience in maps, mobility, local search, POI data, or geospatial systems
• Experience with ranking, recommendations, embeddings, or entity resolution
• Experience with Flink or similar stream processing systems
• Experience reading or making scoped changes in Rust-backed systems

Benefits

• Health care (100% coverage)
• Maternity Leave, Paternity Leave, Second Parent Leave (salary maintained at 100%)
• 8-9 weeks vacation days total per year
• 5 weeks of paid time off
• 1-2 additional weeks RTT
• ~11 bank holidays
• Company shuts down entirely twice a year, two weeks in summer and one week in winter

About the company

amo is growing quickly, and Bump is generating more place and location data every day.