Specialist - Python

About us

WHY LINEDATA ?

Join us in shaping the fintech of tomorrow.

With more than 1,350 colleagues across 20 locations worldwide, you'll help build cutting-edge platforms and tailored services that power the daily operations of 700 leading financial institutions. As a global, multicultural company with over 45 nationalities represented and just as many languages spoken, we thrive on diverse perspectives and collaboration. Together, we tackle future-focused topics like Al and the digitalization of finance, delivering smart solutions for our customers.

Whether you're just beginning your career or are an experienced professional, Linedata offers exposure to large-scale client projects, internal mobility and opportunities to develop your skills alongside leading experts.

Job Summary:
We are looking for a skilled Python developer with hands-on experience in data manipulation and analysis using Pandas. The ideal candidate should have strong problem-solving skills and experience working with large datasets in real-world applications.

Key Responsibilities:

• Write      efficient, scalable Python code for data processing and      transformation.
• Perform      complex data manipulation using Pandas, NumPy, and other scientific      libraries.
• Clean,      transform, and analyze large volumes of structured and unstructured data.
• Develop      scripts and tools to automate workflows.
• Collaborate      with data engineers and analysts to optimize data pipelines.
• Participate      in code reviews and follow best practices in version control (Git).

Required Skills:

• Strong      proficiency in Python, especially with Pandas and NumPy.
• Experience      working with data files in formats like CSV, Excel, JSON, and SQL.
• Familiarity      with Jupyter Notebooks, API integrations, and data visualization tools      (e.g., Matplotlib, Seaborn).
• Experience      with SQL queries and relational databases.
• Good      understanding of software development lifecycle and version control (Git).

Good to Have:

• Exposure      to machine learning libraries (e.g., scikit-learn).
• Experience      with cloud platforms (AWS/Azure/GCP) or data lake frameworks.
• Familiarity      with Airflow, Spark, or other data orchestration tools.