Senior Data Engineer

Amo; Paris; Sur place; EUR 90 000 - 130 000; Plein temps

Avantages offerts par ce poste

Health care 100% coverage

Paris office near Opera

Extended vacation policy

Résumé du poste

amo in Paris is seeking a senior data engineer to build and operate batch and streaming data pipelines, move production data to archival storage, and improve data quality across derived datasets.

You will leverage Python, SQL, PySpark and Spark Streaming, work on Parquet and Iceberg, optimize queries, and collaborate with the team onsite at our central Paris office near Opera.

Qualifications

• 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.

Responsabilités

• 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.

Connaissances

Python

SQL

Scala

Batch processing

Stream processing

Data quality

Observability

Query optimization

Distributed systems

Outils

PySpark

Spark SQL

Spark Streaming

Parquet

Iceberg

Description du poste

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.