Why this role stands out
This remote Senior Manager role offers a fantastic opportunity to drive innovation in clinical data pipelines and build scalable data solutions for a reputable company. You'll thrive here if you are a driven individual with a passion for data engineering and a desire to contribute to impactful clinical research. Apply now to shape the future of data enablement!
Quick overview
Job description
Role: Clinical Data Enablement - Senior Manager
Job Location: USA (Remote)
Objective / Purpose:
The Clinical Data Enablement Senior Manager is responsible for operating and continuously improving end-to-end clinical data pipelines across cloud-based data lake and data warehouse environments. This role builds scalable ingestion and transformation capabilities, partners closely with internal stakeholders and external vendors, and ensures reliable, compliant delivery of clinical data products to downstream consumers
Accountabilities:
- Support end-to-end clinical data pipelines across lake/warehouse environments (build, run, monitor, maintain, troubleshoot) to ensure stable, performant, traceable operations.
- Drive operational excellence through monitoring/alerting, incident management, root-cause analysis, and corrective/preventive actions.
- Build and scale cloud ETL/ELT capabilities (AWS/Azure) for efficient ingestion, transformation, orchestration, and delivery.
- Automate integrations and run operations (scheduling, metadata-driven pipelines, automated quality checks) to improve reliability and timeliness.
- Partner with vendors and cross-functional teams to define data transfer specifications, acceptance criteria, and integration patterns; implement integrations with robust error handling and reconciliation.
- Serve as an SME for structured and unstructured data integration, driving continuous improvements through stakeholder feedback and evolving requirements.
- Partner with downstream teams (Stat Programming, SDTM, Analytics, Clinical Data Programming) to deliver fit-for-purpose datasets and interfaces (format, structure, cadence).
- Ensure on-time, high-quality delivery to agreed specifications; establish and manage SLAs/OLAs as needed.
- Contribute to on‑time, high‑quality delivery against agreed specifications and participate in tracking and reporting operational KPIs (e.g., timeliness, success rate, defects) through dashboards and metrics.
- Help to build the dashboard and metrics for oprational effectiveness
- Design and deliver GxP-aligned clinical data engineering solutions with lifecycle documentation, traceability, and audit-ready evidence.
- Embed data integrity controls (e.g., ALCOA+) and support validated operations via change control, incident/deviation documentation, periodic review, and inspection readiness.
- Collaborate with Quality/Compliance/IT to implement appropriate access controls, logging/audit trails (as applicable), and operating controls.
Education & Competencies (Technical and Behavioral):
- Education/Experience: BS/BA (or equivalent) plus 7+ years in data engineering, pipeline development/operations, and multi-source data integration (clinical/biopharma preferred).
- 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): Hands‑on 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
Interested candidates can email their Resume on
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