Geospatial Data Engineer: Pipelines & Observability (Paris)

amo; Paris; Sur place; EUR 70 000 - 110 000; Plein temps

Avantages offerts par ce poste

Healthcare coverage

Central Paris office

Résumé du poste

amo seeks a data-focused engineer in Paris to build pipelines for place and location data. You will handle noisy real-world signals and large geospatial datasets to improve data quality and observability.

You will prototype in Python, SQL, notebooks, or similar tools, and integrate experiments with backend systems. Experience with PySpark and Spark ecosystems is essential.

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.

Responsabilités

• 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.

Connaissances

Python

SQL

Scala

Geospatial data

Data pipelines

Data quality

Outils

PySpark

Spark SQL

Spark Streaming

Parquet

Iceberg

Description du poste

What You’ll 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.
  
  

Must Have

• 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.
  
  

Life at amo

To ensure that everyone is set up for success within our way of working, we work together onsite 5 days a week.

We wanted to make sure coming to the office was as comfortable as possible for you:

• We chose a location in central Paris, near Opera (Metro lines 3,8,9 and RER A).

• We have a beautiful Parisian-style office with high ceilings, balconies, and huge windows. So a lot of natural light!

Because life outside of work should also be stress-free, we cover:

• Health care (100% coverage).

• Maternity Leave, Paternity Leave, Second Parent Leave (salary maintained at 100%).

• Vacation days: 8-9 weeks (total) per year - (European summer? 🥹😎).

  • 5 weeks of paid time off (by the state);

  • 1-2 additional weeks (RTT, based on our company contract);

  • ~11 bank holidays.

    We shut down entirely twice a year, two weeks in summer and one week in winter to allow everyone to truly recharge and to avoid prolonged slowdowns (especially in the summer). These pauses are part of your total vacation time, giving everyone a real chance to unplug and recharge. No Slack, no email, no FOMO.