Senior Data Engineer
At a glance
Senior Data Engineering role at amo. Paris · full-time · no salary stated · we estimate €60,000–€62,500 across France.
amo has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Develop and operate data flows for both scheduled batch work and continuous streaming
- Transfer live production data into archival or lake storage, with safe handling and clear monitoring
- Set up checks for dataset freshness, completeness, schema validity and quality, while strengthening reliability
- Publish reusable datasets to reduce repeated extraction and aggregation, and tune processing for accuracy, latency and cost
- Test suitable tools before connecting defined experiments to amo’s production systems when needed
What you bring
- You have senior experience creating data pipelines and keeping them running in production
- You are strong in Python and SQL, with production use of Python or Scala
- You have hands-on experience with PySpark, Spark SQL, Spark Streaming, Parquet and Iceberg
- You understand batch and streaming methods, query tuning, distributed systems, data lakes and derived datasets
Who this fits
This role suits a senior data engineer who can work across pipeline operations, storage, query systems and production integration. You’ll work from the Paris office five days a week.
From the employer
amo is growing quickly: more users, more product surfaces, more features, and more data every day. We are looking for a senior data generalist to build the systems that make this data reliable, accessible, and useful across product, business, and compliance needs.
This role is for someone who understands data pipelines deeply, knows the modern data ecosystem, and can work across engines, storage formats, query layers, validation, orchestration, and production integration.
What You’ll Do
Build and maintain batch and streaming data pipelines.
Move production data into archival/data lake storage safely and observably.
Improve quality, reliability, and observability of derived datasets.
Design validations for freshness, completeness, schema correctness, and data quality.
Build reusable datasets that reduce one-off data extraction and aggregation work.
Optimize queries and data processing jobs for correctness, latency, and cost.
Prototype in the right tools, then integrate scoped production experiments with amo’s systems where needed.
Must Have
Senior-level experience building and operating data pipelines.
Strong Python and SQL.
Production experience with Python or Scala.
Experience with PySpark, Spark SQL, Spark Streaming, Parquet, and Iceberg.
Strong understanding of batch and stream processing.
Query optimization experience.
Familiarity with data engine internals and distributed data systems.
Experience with data lakes, table/storage formats, and derived datasets.
Nice To Have
Experience with Flink or similar stream processing systems.
Experience with ML training or inference pipelines.
Familiarity with ranking, recommendations, embeddings, or entity resolution.
Experience with privacy-sensitive data systems, GDPR workflows, or data deletion/export pipelines.
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.
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