Data Engineer

Job Description Our pharmaceutical client is seeking a skilled and proactive Data Engineer to join our team and help drive the automation and scalability of our data workflows. This role is ideal for someone with a strong foundation in data engineering who thrives in a fast-paced environment and can work independently while collaborating across teams. You’ll play a key role in evolving our data architecture, automating critical processes, and supporting cross-functional data needs. This position offers the opportunity to work with cutting-edge technologies like Databricks, GitHub Actions, and CI/CD pipelines, while contributing to impactful projects in the pharmaceutical and cloud computing space. Key Responsibilities: • Design, build, and maintain scalable data pipelines and workflows. • Automate various points in the data architecture to improve efficiency and reliability. • Collaborate with stakeholders to understand end-to-end data workflows and identify opportunities for optimization. • Support project scaling initiatives, ensuring robust and maintainable data infrastructure. • Provide occasional support to team members (e.g., Deepak and Maisy) for data requests, updates, and troubleshooting. • Contribute to the migration and automation of data processes into Databricks. • Ensure best practices in version control and deployment using GitHub and CI/CD pipelines. Required Skills & Experience: • 5–7+ years of experience in data engineering. • Strong proficiency in SQL and data modeling. • Hands-on experience with CI/CD pipelines, especially in conjunction with GitHub. • Familiarity with GitHub Actions for automation and deployment. • Experience working with Databricks for data processing and analytics. • Solid understanding of cloud computing platforms (e.g., AWS, Azure, GCP). • Background or experience in pharmaceutical data is a plus. • Ability to work independently and manage multiple priorities effectively. Preferred Qualifications: • Experience with data governance and compliance in regulated industries. • Familiarity with Python, Spark, or other data engineering tools. • Strong communication and collaboration skills.