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Senior DataOps Engineer (M/F)

Original title: DATAOPS Engineer Senior (F/H)

Ternair · Lille, France · Hybrid · Senior

  • Lille, France · Hybrid
  • French

Indexed (today) · refreshed constantly

Budget
€50–63 / h
Start
flexible
Work mode
Hybrid
Contract
Freelance / B2B
Seniority
Senior

Required skills

Nice to have:RetailRetail Media

Languages: French

Job description

Seeking a Senior DataOps Engineer Freelancer to support data teams in accelerating and securing their deliveries by defining standards, deploying tools, and automating processes.

Project overview

To support its data teams in feature teams, our client is looking for

⚙️ a Senior DataOps Engineer Freelancer (M/F).

📌 Context:

Its data organization is structured into autonomous feature teams, composed notably of Data Analysts and Data Scientists.

🎯 Your role:

You will support Data Analysts and Data Scientists to accelerate and secure their deliveries. You will define standards, deploy tools, and automate processes to ensure code and data quality, consistency of practices, reliability of production deployments, and cost control.

🤸‍♂️ Your missions:

Define and promote common development standards

Implement appropriate processes

Create templates and guidelines,

Reduce feature and data duplication.

Standardize CI/CD pipelines for data artifacts (Databricks jobs, Spark Declarative Pipelines, BigQuery)

Define environments and associated validation processes.

Support Data Analysts and Data Scientists in their production deployments (pair programming, reviews, validation).

Identify and reduce technical debt.

Contribute to the evolution of the Terraform infrastructure.

Analyze consumption patterns (Databricks clusters and BigQuery queries)

Identify redundant or suboptimal flows

Raise awareness among teams about good performance practices.

Implement testing and monitoring strategies on data pipelines

Tooling for anomaly detection and data traceability.

Structure the model lifecycle with MLflow (versioning, registry, deployment).

Support Data Scientists on MLOps best practices and in defining the development and production process.

Tooling for model monitoring (drift, performance).

🚀 Technical Stack:

  • Code quality and standards:
  • Production deployment process:
  • Cost optimization and control:
  • Data quality:
  • MLOps:
  • Data platform: Databricks / Spark, Google Cloud Platform
  • Pipelines & frameworks: Spark Declarative Pipelines (SparkSQL / PySpark), internal PySpark framework, PySpark and Scala notebooks, BigQuery
  • Languages: Python (OOP), SQL, Scala (legacy)
  • Orchestration: Airflow
  • Delivery: GitHub, Docker, OpenTofu / Terraform, MLflow

Nice to have

Knowledge of the Retail and Retail Media domain.

📍 Modalities:

Status: freelance

Start date: as soon as possible

Project details

Lille

  • Start: flexible
  • Remote: hybrid
  • Location: Lille, France, FR
  • Rate: 50-63 EUR/h
  • Languages: French

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