Data Engineer

Beghou brings over three decades of experience helping life sciences companies optimize their commercialization through strategic insight, advanced analytics, and technology. From developing go-to-market strategies and building foundational data analytics infrastructures to leveraging artificial intelligence to improve customer insights and engagement, Beghou helps life sciences companies maximize performance across their portfolios. Beghou also deploys proprietary and third-party technology solutions to help companies forecast performance, design territories, manage customer data, organize, and report on medical and commercial data, and more. Headquartered in Evanston, Illinois, we have 10 global offices.

Our mission is to bring together analytical minds and innovative technology to help life sciences companies navigate the complexity of health care and improve patient outcomes.

This role is responsible for building, optimizing and supporting Beghou’s AI forward data platform. This role requires hands on development in Databricks, Python/Pyspark and cloud environments (AWS or Azure), while adhering to software engineering, CI/CD and security best practices.

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.

Preferred Qualifications

• 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.