Data Management & Engineering
Advanced Techniques
Build containers and Helm charts
- Basic understanding of containerization concepts and Helm charts
- Ability to assist in creating and deploying containers
- Familiarity with container orchestration tools (e.g., Kubernetes)
- Proficiency in building and managing containers and Helm charts
- Independently create and deploy containers
- Implement container orchestration solutions
- Strategic oversight of containerization strategies and Helm chart management
- Lead the development of containerization policies and best practices
- Ensure compliance with containerization standards and regulations
Build event-driven workloads for NLP
- Basic understanding of event-driven architecture and NLP concepts
- Familiarity with event processing frameworks (e.g., Apache Kafka)
- Proficiency in building and managing event-driven workloads for NLP
- Implement event processing solutions for NLP workloads
- Strategic oversight of event-driven architecture and NLP workload management
- Ensure compliance with event-driven architecture standards and regulations
Building and writing viable clinical code sets
- Basic understanding of clinical code sets and their importance
- Familiarity with clinical data standards and regulations to build and write a viable clinical code sets
- Can expertly build and write clinical code sets
- Implement clinical data standards in code set development
- Strategic oversight of clinical code set development and management
- Ensure compliance with clinical data standards and regulations
Data engineering for OMOP using dbt/SQLMesh
- Ability to assist in data engineering tasks using dbt/SQLMesh
- Familiarity with OMOP data models and standards
- Proficiency in using dbt/SQLMesh for data engineering tasks
- Independently perform data engineering tasks using dbt/SQLMesh
- Implement OMOP data models and standards in data engineering projects
- Strategic oversight of data engineering projects using dbt/SQLMesh
- Lead the development of data engineering strategies and best practices
- Ensure compliance with OMOP data standards and regulations
Developing Architecture based on requirements
- Understands a highlevel set of components that delivers clients expressed requirements e.g. servers for hosting web applications
- Understands a set of components that delivers clients expressed requirements and can identify additional components that provide functionality that a client may not realise is required e.g. a network firewall to protect web application servers. They have an awareness of networking, security, regulatory, compliance, backup, restore
- Can specify a comprehensive architecture that addresses the clients expressed and implied requirements, and understands additional elements such as networking, security, regulatory, compliance, backup and restore
Data Governance
Column Storage Databases
- Is able to explain column storage database concepts and can use tools to do basic commands
- Familiarity with data governance standards and practices
- Is proficient in configuring and managing column storage databases
- Implement data governance standards in column storage database management
- Strategic oversight of column storage database management strategies
- Ensure compliance with data governance standards and regulations
Data Orientated Infrastructure
Data Catalogue
- Basic understanding of data cataloguing concepts and tools (e.g., )
- Can input, maintain , validate metadata in data catalogues.
- Familiarity with metadata standards and practices
- Profiency in creating and managing data catalogues
- Independently develop and maintain data catalogues
- Implement metadata standards in data cataloguing
- Strategic oversight of data cataloguing strategies and management
- Lead the development of data catalogue policies and best practices
- Ensure compliance with metadata standards and regulations
Data visualisation
- Can use data visualisation libraries such as plotly to visualise data
- Can use data visualisation libraries such as plotly to generate interactive data visualisations
- Can use data visualisation platforms such as power bi to create dashboards to show related visualisations on single applications
Pipelines and permissions
- Is able to apply basic knowledge of pipelines to assist in the development of simple pipelines to extract, manipulate and load data
- Familiarity with data security and privacy regulations. Can set permissions for pipeines appropriate to usage.
- Proficiency in configuring and managing data pipelines and applying appropriate permissions
- Implement data security measures in pipeline and permission management
- Strategic oversight of data pipeline and permission management strategies
- Ensure compliance with data security and privacy regulations
Understanding the data types
- Basic understanding of different data types and their characteristics
- Ability to assist in identifying and categorizing data types
- Proficiency in managing and processing various data types
- Independently identify and categorize data types
- Strategic oversight of data type management and processing strategies
- Lead the development of data type management policies and best practices
Data Analysis & Infrastructure
Data mapping, Standards and Interoperability
- Can describe the usage of basic data mapping concepts and standards
- Has an awareness with data analysis tools and techniques (e.g., )
- Can explain the importance of data quality and consistency
- Can implement data mapping and ensure interoperability between systems, coding systems, and data sources
- Can analyze data to ensure it meets standards and interoperability requirements
- Can ensure data quality and consistency across systems
- Can lead data mapping projects and ensure compliance with industry standards
- Can oversee data analysis processes to ensure compliance and interoperability
- Can lead initiatives to improve data quality and consistency across the organization