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Company

Original Job Post

BioSpace · 3 days ago

Senior Data Engineer

North Chicago, IL

Full-time

Onsite

Senior Level

3+ years exp

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Comp. & Benefits

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Responsibilities

Collaborates with the Data Scientists and cross-functional data stewards to identify appropriate data sources and to enable streamlined data flow for the Data Science and Analytics capabilities across clinical development.

Develop, construct, test and maintain architectures (such as databases and large-scale process systems) to support strategic projects within Clinical Development

Build data products and processes which perform data transformation, metadata extraction, workload management and error processing and management.

Implement standardized, automated operational and quality control processes to deliver accurate and timely data and reporting.

Adhere to best practices for coding, testing and designing reusable code/component.

Contribute to the discovery and understanding of new tools, techniques and technologies to change course as needed.

Develop solutions to improve data reliability, efficiency and quality.

Ensures adherence to federal regulations and applicable local regulations, Good Clinical Practices (GCPs), ICH Guidelines, AbbVie Standard Operating Procedures (SOPs), and to functional quality standards. Stays abreast of new and/or evolving local regulations, guidelines and policies related to clinical development.

Self-starter, comfortable with ambiguity, experience initiating and driving projects with minimal oversight and guidance.

Establish and follow data science and engineering best practices including peer review, code review, documentation, coding standards, data quality and ensure reproducibility and compliance.

Highly autonomous and productive in accomplishing the deliverables with minimal direction.

Qualification

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SQLPythonData AnalysisCloud ComputingAWSAzureETLAirflowData VisualizationIaaSSolution ArchitectureData ProcessingSparkScalaContainerizationDevOpsDockerKubernetesData ScienceAdvanced AnalyticsMachine LearningStatistical ModelsBiotechPharmaExecution ManagementProblem-SolvingCommunicationPresentationTime Management

Required

MS or PhD in computer science or other quantitative disciplines with 3-5 years of experience.

3+ years of hands-on experience in advanced SQL, Python, or R.

Experience delivering Data and Analytical initiatives on modern cloud-based data warehouse solutions, cloud computing and cloud operations preferably AWS and/or Azure.

Preferred

Experience with ETL, scheduling and orchestration tools like Airflow is preferred.

End-to-end experience with data, including querying, aggregation, analysis, and visualization; Fluency in both structured and unstructured data is preferred.

Experience with IaaS(Infrastructure as Code) and general understanding of end-to-end solution architecture for data science and advanced analytics solutions is preferred.

Experience with large scale data processing and distributed computing using Spark/Scala is a plus.

Experience with containerization, DevOps methodologies, Docker/Kubernetes ecosystem is a plus.

Experience in Data Science and Advanced Analytics domain is preferred.

Familiarity and general understanding of Machine Learning and statistical models is preferred.

Biotech / Pharma experience is a plus.

Good communication and presentation skills, being able to explain complex problems and the solutions applied, and comfortable in presenting technical solutions to a nontechnical audience.

Demonstrated history of successful execution in a fast-paced environment and in managing multiple priorities effectively.