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Salary
≈ $37k – $72k per year (Estimated)
Location
In office (Singapore)
Seniority
Junior · 2+ years exp
Employment
Contractor

Confirmed on the employer's own hiring board on Oct 23, 2026. First seen by Alion on Oct 19, 2026. Crédit Agricole S.A. scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Crédit Agricole S.A. is the listed central entity of the French cooperative banking group Crédit Agricole, headquartered in Montrouge near Paris, covering retail banking, corporate and investment banking, asset management, insurance and payment services. It controls business lines such as Crédit Agricole CIB, Amundi, Crédit Agricole Assurances and LCL, and its recruiting covers teams in Paris, Guyancourt, Luxembourg, New York, Montreal and Malaysia as well as across France. Its openings include transaction banking IT and operations roles, quantitative analysts, business analysts, back-office technicians, HR business partners and many internships.

Business type

Types of Jobs - IT, Digital et Data

Job title

Junior Data Engineer

Contract type

Fixed-Term Contract

Job summary

Position

In a challenging and multicultural environment, we are looking for a Data Engineer to join our Digital Excellence Centre (DEC) department of Crédit Agricole CIB. The department handles the development of transversal and international projects.

The ideal candidate is a Python programmer with hands-on experience building data pipelines and integrating data workflows to support ML and analytics use cases. You'll work closely with data engineers, ML engineers, and analysts to design, build, and maintain scalable data pipelines that are robust and production ready.

Main responsibilities

§ Design and develop data ingestion, transformation, and delivery pipelines using Python and modern ETL tools.

§ Build backend services, APIs or UIs (if ReactJS experience is present) to support ML applications

§ Maintain and optimize batch and real-time data pipelines for performance and scalability

§ Support the packaging and deployment of machine learning models into production environments.

§ Write clean, modular, testable code and participate in code reviews.

§ Collaborate with data scientists, engineers and DevOps teams to scalable and reliable data pipeline.

§ Support data exploration, feature engineering, and occasional model building where needed.

§ Automate data validation, quality checks, and pipeline monitoring.

§ Work with cloud platforms and container technologies (Docker, Kubernetes)

§ Follow best practices for versioning, logging, and CI/CD.

Qualifications and Profile

Mandatory:

§ Have Graduate or Master’s degree in the relevant field of AI / ML / Data.

§ 2+ years of experience in software development, ML engineering, or data pipeline engineering.

§ Strong programming skills in Python (pandas, scikit-learn, FastAPI or Flask)

§ Familiarity with SQL and working with relational databases or cloud data warehouses (e.g., BigQuery, Snowflake, Redshift).

§ Knowledge on NoSQL databases (any experience in Graph database is desirable)

§ Hands-on with data pipeline tools like Apache Airflow, Luigi, or similar tools.

§ Experience with version control (Git), testing, and agile development practices.

§ Experience with CI/CD pipelines and containerization (Docker, Kubernetes).

§ Exposure to cloud environments (AWS, GCP, or Azure) and containerization (Docker).

§ Strong debugging and problem-solving skills.

Preferred skills:

§ Experience in ReactJS or building frontend components for ML dashboards or monitoring tools.

§ Exposure to streaming data (e.g., Kafka, Spark Streaming).

§ Familiarity with MLOps tools like MLflow, TFX, or Seldon.

§ Basic understanding of machine learning concepts and model deployment lifecycle

Supplementary Information

Other Professional Skills and Mind-set

§ Ability and willingness to learn and adopt new technologies

§ Strong organizational and communication skills

§ Strong analytical and problem solving skills

§ Awareness of various software development procedures

§ Ability to follow defined procedures

§ Understanding and respect of cultural diversity

Minimal education level

Bachelor Degree / BSc Degree or equivalent

Academic qualification / Speciality

Bachelor and above in relevant discipline

Level of minimal experience

0-2 years

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