- Company Name
- SULLY GROUP
- Job Title
- Ingénieur de données/Ingénieure de données
- Job Description
-
**Job Title:**
Data Engineer
**Role Summary:**
Lead technical development of data solutions in Python for a Data Services Center. Design, build, and deploy scalable data pipelines, analytics, and visualizations using advanced libraries and SQL. Serve as a technical reference on client projects, ensuring architectural rigor, code quality, and best practices.
**Expectations:**
- Architect and implement end‑to‑end data solutions that meet client business goals.
- Mentor and review work of junior developers, promoting clean code and reproducibility.
- Communicate complex technical concepts clearly to project leaders and clients.
- Stay current with emerging data technologies and propose innovative solutions.
**Key Responsibilities:**
- Design data models, ETL workflows, and analytics pipelines in Python (Pandas, Polars, Dask, Airflow, Sci‑Kit‑Learn).
- Write advanced SQL queries for PostgreSQL, DuckDB, and other relational or analytical databases.
- Develop dashboards and visualizations with Matplotlib, Dash, Streamlit, or Apache Superset.
- Build, containerize, and orchestrate services using Docker, Docker‑Compose, GitLab CI/CD, Kubernetes, and NGINX.
- Conduct code reviews, enforce coding standards, and maintain documentation.
- Collaborate with project managers and clients to define requirements, validate deliverables, and ensure alignment with business objectives.
**Required Skills:**
- Proficiency in Python for data engineering; strong command of Pandas; experience with Polars, Dask, Airflow, and Sci‑Kit‑Learn.
- Advanced SQL knowledge, especially PostgreSQL; familiarity with Superset or DuckDB is a plus.
- Hands‑on experience with Docker, Docker‑Compose, GitLab CI/CD, Kubernetes, and NGINX.
- Ability to develop web interfaces (Flask, FastAPI, Django) is desirable.
- Excellent communication, collaboration, and problem‑solving skills.
- Self‑driven, curious, and proactive in exploring new tools and techniques.
**Required Education & Certifications:**
- Bachelor’s (or Master’s) degree in Computer Science, Data Science, Software Engineering, or a related field.
- Minimum 3 years of professional experience in data engineering or related roles; experience on large, client‑facing projects is preferred.
- Certifications in Cloud platforms (AWS, GCP, Azure), Docker/Kubernetes, or Databricks are advantageous but not mandatory.