Data Engineer

Role Description:

The Data Engineer is a key contributor to the Clinical Trial Data & Analytics (CTDA) Team, driving the development of robust data pipelines and platforms to enable advanced analytics and decision-making. Operating within a SAFE Agile product team, this role ensures system performance, minimizes downtime through automation, and supports the creation of actionable insights from clinical trial data.

Collaborating with product owners, architects, and engineers, the Data Engineer will implement andenhance analytics capabilities. Ideal candidates are detail-oriented professionals with strong technical skills, a problem-solving mindset, and a passion for advancing clinical operations through data engineering and analytics.

Roles & Responsibilities:

• Proficiency in developing interactive dashboards and visualizations using Spotfire, Power BI, and Tableau to provide actionable insights.

• Expertise in creating dynamic reports and visualizations that support data-driven decision-making and meet stakeholder requirements.

• Ability to analyze complex datasets and translate them into meaningful KPIs, metrics, and trends.

• Strong knowledge of data visualization best practices, including user-centric design, accessibility, and responsiveness.

• Experience in integrating data from multiple sources (databases, APIs, data warehouses) into visualizations.

• Skilled in performance tuning of dashboards and reports to optimize responsiveness and usability.

• Ability to work with end-users to define reporting requirements, develop prototypes, and implement final solutions.

• Familiarity with integrating real-time and predictive analytics within dashboards to enhance forecasting capabilities.

Basic Qualifications and Experience:

• Master’s degree and 1 to 3 years of Computer Science, IT or related field experience  OR

• Bachelor’s degree and 3 to 5 years of Computer Science, IT or related field experience OR

• Diploma and 7 to 9 years of Computer Science, IT or related field experience

Functional Skills:

Must-Have Skills:

• Proven hands-on experience with cloud platforms such as AWS, Azure, and GCP.

• Proficiency in using Python, PySpark, and SQL, with practical experience in ETL performance tuning.

• Development knowledge in Databricks.

• Strong analytical and problem-solving skills to tackle complex data challenges, with expertise in using analytical tools like Spotfire, Power BI, and Tableau.

Good-to-Have Skills:

• Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops

• Familiarity with SQL/NOSQL database, vector database for large language models

• Familiarity with prompt engineering, model fine tuning

Professional Certifications 

• AWS Certified Data Engineer (preferred)

• Databricks Certification (preferred)

• Any SAFe Agile certification (preferred)

Soft Skills:

• Excellent critical-thinking and problem-solving skills 

• Strong communication and collaboration skills

• Demonstrated awareness of how to function in a team setting

• Demonstrated presentation skills