Senior Data Engineer
We are looking fora an experienced Senior Data Engineer to join the Real World Evidence team.
The Senior Data Engineer will be responsible for building and maintaining the Real-World Evidence data lake and implementing data migration processes with proper structuring and integration. Tasks include parsing EMR resources, developing or configuring tools for efficient data annotation, writing scripts to detect discrepancies, and monitoring data coverage and quality metrics. Additionally, building dashboards to aggregate key data points, assist data annotators in prioritizing and simplifying their work, manage access control security policies, and perform data analytics tasks.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
Design, develop, and maintain scalable data pipelines and ETL processes.
Collaborate with clinicians, data quality experts, and other stakeholders to understand data requirements and deliver solutions.
Ensure data quality, integrity, and security across all data platforms.
Optimize and improve existing data systems for performance and scalability.
Implement data governance and best practices for data management.
Monitor and troubleshoot data pipeline issues to ensure smooth operations.
Program data validations and quality checks to ensure data integrity.
Define, implement, and review data quality metrics; perform trend analyses; identify and support the resolution of data issues.
Support the interrogation, analytics, and reporting of clinical real-world data.
Support research-specific quality audits and regulatory authority inspections, acting as a subject matter expert.
The Senior Data Engineer will be responsible for building and maintaining the Real-World Evidence data lake and implementing data migration processes with proper structuring and integration. Tasks include parsing EMR resources, developing or configuring tools for efficient data annotation, writing scripts to detect discrepancies, and monitoring data coverage and quality metrics. Additionally, building dashboards to aggregate key data points, assist data annotators in prioritizing and simplifying their work, manage access control security policies, and perform data analytics tasks.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
Design, develop, and maintain scalable data pipelines and ETL processes.
Collaborate with clinicians, data quality experts, and other stakeholders to understand data requirements and deliver solutions.
Ensure data quality, integrity, and security across all data platforms.
Optimize and improve existing data systems for performance and scalability.
Implement data governance and best practices for data management.
Monitor and troubleshoot data pipeline issues to ensure smooth operations.
Program data validations and quality checks to ensure data integrity.
Define, implement, and review data quality metrics; perform trend analyses; identify and support the resolution of data issues.
Support the interrogation, analytics, and reporting of clinical real-world data.
Support research-specific quality audits and regulatory authority inspections, acting as a subject matter expert.
Requirements:
Qualifications:
Bachelors degree or higher, preferably in an engineering-related field (Computer Science/Statistics/Engineering).
Knowledge:
At least 3 years of proven experience as a Data Engineer or in a similar role.
Proficiency in SQL and experience with relational databases.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
Strong programming skills in languages like Python, Java, or Scala.
Knowledge or experience in handling clinical data.
Excellent verbal and written communication skills, capable of providing clear, concise, timely, and relevant information.
Strong ability to identify and resolve complex challenges using critical thinking skills.
Exceptional organizational and record-keeping skills with keen attention to detail, precision, and accuracy.
Ability to manage and prioritize multiple tasks simultaneously, proactively solve problems, and handle competing priorities and deadlines.
Demonstrated ability to work effectively in a diverse team, including analysts, clinicians, and engineers.
Familiarity with EMR data and FHIR resources advantage.
Qualifications:
Bachelors degree or higher, preferably in an engineering-related field (Computer Science/Statistics/Engineering).
Knowledge:
At least 3 years of proven experience as a Data Engineer or in a similar role.
Proficiency in SQL and experience with relational databases.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
Strong programming skills in languages like Python, Java, or Scala.
Knowledge or experience in handling clinical data.
Excellent verbal and written communication skills, capable of providing clear, concise, timely, and relevant information.
Strong ability to identify and resolve complex challenges using critical thinking skills.
Exceptional organizational and record-keeping skills with keen attention to detail, precision, and accuracy.
Ability to manage and prioritize multiple tasks simultaneously, proactively solve problems, and handle competing priorities and deadlines.
Demonstrated ability to work effectively in a diverse team, including analysts, clinicians, and engineers.
Familiarity with EMR data and FHIR resources advantage.
This position is open to all candidates.
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