Mid-level Python Developer French-speaking (m/f)
ARHS Group, part of Accenture, is looking for a Mid-level Python Developer (m/f) to join one of our client teams onsite in Luxembourg within the manufacturing sector.
In this role, you will contribute to the extraction, processing, and analysis of large datasets, helping transform raw data into valuable business insights. You will work closely with technical and business stakeholders on data-driven initiatives and analytical projects.
THE WORK:
- Develop and maintain Python applications for data extraction, transformation, and processing.
- Work with large datasets stored in SQL databases.
- Design and optimize data queries and processing workflows.
- Analyze data and contribute to the development of analytical solutions.
- Collaborate with business and technical teams to understand requirements and deliver effective solutions.
- Support testing, troubleshooting, and continuous improvement activities.
- Produce and maintain technical documentation.
Onsite at client site: This role requires an onsite presence with our clients and partners to support project delivery and strengthen client relationships.
Our roles require in-person time to encourage collaboration, learning, and relationship-building with clients, colleagues, and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.
HERE’S WHAT YOU’LL NEED:
- Minimum 3 years of experience in Python development.
- Strong knowledge of Python and SQL.
- Experience working with data extraction, processing, and analysis.
- Good understanding of relational databases and data structures.
- Strong analytical and problem-solving skills.
- Ability to work independently and collaboratively within a team.
- Fluency in French & English (written and spoken).
BONUS POINTS IF YOU HAVE:
- Interest in data analytics, data science, or industrial data processing.
- Academic background or strong knowledge in mathematics (e.g., matrices, integrals, statistics).
- Experience with data visualization or scientific computing libraries.
- Experience working in manufacturing, industrial, or engineering environments.