Data Analyst Anglophone

Description de l'entreprise

ALTEN DELIVERY CENTER MAROC, Subsidiary of the world leader in engineering and technology consulting created in 2008 and present in Fez, Rabat, Tetouan and Casablanca, today has more than 2,300 consultants and is aiming for a center of excellence of 3,100 consultants ALTENiens at the end of 2024. With more than 90 recruitments per month, ALTEN Maroc is now a major player in the professional integration of engineers. We support our clients, industry leaders, in their development strategies in the fields of automotive, rail, IT, R&D and Telecoms & Media.

Joining ALTEN MAROC means benefiting from :

· Diversified professional paths with career opportunities, internal, sectoral, geographic and professional mobility.

· Certification and diploma training courses.

· Regular events to combine well-being and performance.

Description du poste

The consultant will be responsible for the following tasks :

• Collaborate with cross-functional teams (including Data Scientists, Analysts, Developers) to define data requirements, pipeline design, and solutions. 
• Design, implement, and maintain scalable ETL pipelines using AWS Glue (Spark), Python, and PySpark. 
• Manage complex data workflows and dependencies, including with AWS Lambda, using Airflow (or similar orchestration tools). 
• Build and maintain cloud-native, scalable, and cost-effective data infrastructure on AWS, ensuring performance optimization. 
• Integrate and optimize data flows across various AWS services like S3 (Glue Catalog, Athena), Aurora Postgres, Redshift, and Iceberg tables. 
• Ensure data quality, governance, and compliance standards are met across all data processes. 
• Take ownership of the end-to-end lifecycle of data pipelines, from design to deployment and monitoring. 
• Collaborate closely with Data Science teams to operationalize models, leveraging AWS Sagemaker where applicable. 
• Ensure strong documentation practices and follow best practices for scalability, maintainability, and cost management.

Qualifications

• Master’s degree in Data 
• 5 years of experience in a similar role 

Mandatory Hard skills : 
Python & Spark 

• Proficiency in Python (including Pandas) for data transformations using TDD approach. 
• Hands-on experience with Apache Spark, ideally via AWS Glue. 

Cloud Services (AWS) 

• Experience with AWS services such as S3, Glue, Athena, Redshift, Aurora, Lambda, IAM, and EventBridge. 
• Comfortable with cloud-based architecture, serverless design, and deployment strategies. 

Data Workflow Orchestration 

• Experience in building and managing DAGs in Airflow (or similar tools).
• Familiarity with Lambda-based event-driven architectures. 

Software Engineering Practices 

• Proficiency with Git (branching, pull requests, code reviews) and CI/CD pipelines.
• Understanding of release management and automated testing in a multienvironment setup. 

Big Data Ecosystems 

• Hands-on experience with distributed processing frameworks (like Spark) and large-scale data lake solutions, including Iceberg tables. 
• Familiarity with data lake architectures, partitioning strategies, and best practices. 

Hard skills that would be a real plus : 

• Experience with dimensional modelling, partitioning strategies, or other best practices. 
• SQL knowledge for properly designing and maintaining data schemas for efficient querying and reporting 
• Infrastructure as a code: Familiarity with tools like Terraform or CloudFormation for automated AWS provisioning. 
• Event-Driven Architectures: Experience with event-driven architectures and working with AWS EventBridge / Lambda / SQS / SNS

Soft skills : 

• Effective communication skills for scrum team collaboration 
• Ownership & Accountability: Drive projects independently and take full responsibility for deliverables. 
• Effective Communication: Ability to explain technical details to both technical and non-technical stakeholders. 
• Strong Problem-Solving: Ability to dissect complex issues, propose scalable solutions, and optimize workflows. 
• Team Collaboration: Comfortable working with cross-functional teams (Data Scientists, Developers, Analysts, etc.). 
• Adaptability & Continuous Learning: Eagerness to explore emerging technologies and refine existing processe