We're looking for a Data Engineer who is passionate about modern data platforms, cloud technologies, and AI-enabled development. In this role, you'll design, build, optimize, and support our next-generation AI-forward data platform, enabling scalable, secure, and high-performance data solutions that power advanced analytics and machine learning.
If you thrive in a collaborative environment and enjoy solving complex technical challenges.
We'll Trust you to:
- Design, develop, optimize, and support Beghou's AI-forward data platform.
- Build scalable data pipelines and ETL/ELT workflows using Databricks, Python, and PySpark.
- Develop cloud-native data solutions on AWS and/or Azure.
- Implement software engineering best practices, including CI/CD, version control, automated testing, and secure development practices.
- Optimize data processing performance, reliability, and scalability.
- Collaborate with data scientists, software engineers, and business stakeholders to deliver high-quality data products.
- Apply cloud security and identity management best practices across the platform.
- Evaluate and incorporate AI tools into development workflows to improve engineering productivity and solution quality.
- Contribute to continuous improvement of engineering standards, architecture, and platform capabilities.
You'll need to have:
- Bachelor's or advanced degree in Computer Science, Engineering, Data Science, Statistics, or a related quantitative field.
- 3+ years of professional data engineering experience.
- Strong programming experience with Python, including pandas and/or PySpark.
- Hands-on experience with Databricks and modern cloud platforms (AWS and/or Azure).
- Strong experience with relational databases such as PostgreSQL, Oracle, MySQL, Amazon Redshift, or Snowflake.
- Experience using Git-based source control and modern CI/CD practices.
- Experience with identity and access management technologies such as Azure AD, Okta, OAuth, or SAML.
- Knowledge of cloud security best practices.
- Experience with ETL platforms such as Azure Data Factory, Informatica, SnapLogic, or Boomi.
- Experience with containerization technologies including Docker, Kubernetes, or AWS ECS.
- Experience developing web applications using Flask, Django, JavaScript, HTML/CSS, or Ajax.
- Experience incorporating AI-assisted development tools into engineering workflows.
- Industry certifications such as:
- Databricks Certified Data Engineer
- AWS Certified Data Engineer
- Microsoft Azure/Fabric Data Engineer
- Google Cloud Professional Data Engineer
- Experience in the life sciences, healthcare, or pharmaceutical industry.