Clinical Data Engineer

Role & responsibilities

• Core skills: Strong SQL, data modeling, and data quality controls; working knowledge of NoSQL and integration patterns.
• Programming/SDLC: Proficiency in Python (preferred) or R; experience building production pipelines (testing, logging, monitoring); familiarity with SDLC practices; Jira/Confluence required.
• Data Standards: Knowledge of CDISC, CDASH, and SDTM standards preferred.
• Visualization & Reporting (for Reporting role): Handson experience designing and supporting operational dashboards and data visualizations using tools such as Power BI, Tableau, and/or QlikView, with an understanding of data refresh, access controls, and performance considerations.
• Data Formats and Interfaces: Hands-on with CSV, JSON, XML, and API/file-based integrations.
• Cloud/platforms: Cloud experience (e.g., AWS such as EC2/EMR/RDS/Redshift/Apache Spark) and related platforms (e.g., Snowflake, Databricks). Pipeline and platform expertise: reusable ELT/ETL frameworks; data warehouse/data lake technologies (e.g.,Snowflake,Amazon Redshift); large-scale pipeline performance and maintenance.
• DevOps: GitHub/GitLab version control; CI/CD exposure preferred.
• GxP & Data integrity: Experience working in GxP-regulated environments with change control/audit readiness expectations; ability to embed data integrity controls into pipelines and operations.
• Ways of working: mentor junior engineers/FSPs; independent and collaborative problem-solving; ability to prioritize in a fast-paced environment and deliver to deadlines.
• Working style: Strong collaboration and communication; organized, self-directed, proactive problem-solver.
• Prior regulatory inspection experience preferred.
• Preferred: AWS/Azure and/or Python certification.
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