Data Engineer II (SAS)

About the role

The Data Engineer II will work closely with clients to provide technical consulting, configure the elluminate® platform and develop custom analytics for clinical trial projects. You will be responsible for trial configuration, quality control, system validation and integration of clinical software solutions.

Key responsibilities

• Deliver technical consulting services and configure the elluminate® platform for multiple clients.
• Guide and support a team of data engineers on service‑delivery activities.
• Design, develop, test and deploy efficient SQL code for SDTM, custom reports and visualizations using MS SQL, elluminate® Mapper and Qlik.
• Provide proactive technical support for client‑reported tickets and manage multiple timelines and deliverables.
• Facilitate client onboarding workshops and training sessions on the elluminate® platform.
• Configure, migrate and support the elluminate® platform for assigned clients, maintaining specifications and quality‑control documents.

Required profile

• 3+ years of professional experience, preferably in a pharmaceutical or life‑science environment.
• Bachelor's degree or equivalent experience.
• Experience designing and developing back‑end database/warehouse architectures.
• Ability to work with cross‑functional technical teams and demonstrate proactive, logical thinking.
• Strong verbal and written communication skills in English.
• Understanding of clinical trial data standards such as CDISC ODM, SDTM or ADaM is a plus.

Required skills

• Proficient in SQL, T‑SQL and PL/SQL.
• Familiar with Oracle, SQL Server, Teradata and DB2 databases.
• Experience with data‑reporting tools: QlikSense, QlikView, Spotfire, Tableau, Business Objects, Cognos, MicroStrategy, IBM DataStage, Informatica, Spark.
• Knowledge of programming languages and concepts.NET, C#, Python, R, Java, HTML, SSRS.
• Experience with cloud platforms (AWS, Azure) and REST APIs.
• Understanding of big‑data, ETL, data pipelines, data modelling, data analytics, BI, data warehouse and data lake concepts.