The global skills and competency framework for the digital world

Data engineering DENG

(unchanged)

Designing, building, operationalising, securing and monitoring data pipelines and data stores.

SFIA 9 is in development

  • SFIA 9 beta due in early July 2024
  • SFIA 9 planned for publication October 2024

This is a prototype for SFIA 9. It is subject to change before publication.

Guidance notes

(new)

Activities may include, but are not limited to:

  • identifying data sources, data processing concepts and methods
  • evaluating, designing and implementing on-premise, cloud-based and hybrid data engineering solutions
  • structuring and storing data for uses including, but not limited to, analytics, machine learning, data mining, sharing with applications and organisations
  • harvesting structured and unstructured data
  • integrating, consolidating and cleansing data
  • migrating and converting data
  • applying ethical principles in handling data
  • ensuring appropriate storage of data in line with relevant legislation
  • building in security, compliance, scalability, efficiency, reliability, fidelity, flexibility and portability.

Understanding the responsibility levels of this skill

Where lower levels are not defined...

  • Specific tasks and responsibilities are not defined because the skill requires a higher level of autonomy, influence, and complexity in decision-making than is typically expected at these levels. You can use the essence statements to understand the generic responsibilities associated with these levels.

Where higher levels are not defined...

  • Responsibilities and accountabilities are not defined because these higher levels involve strategic leadership and broader organisational influence that goes beyond the scope of this specific skill. See the essence statements.

Developing skills and demonstrating responsibilities related to this skill

The defined levels show the incremental progression in skills and reponsibilities.

Where lower levels are not defined...

You can develop your knowledge and support others who do have responsibility in this area by:

  • Learning key concepts and principles related to this skill and its impact on your role
  • Performing related skills (see the related SFIA skills)
  • Supporting others with tasks (generic examples are provided by the essence statements for each level)

Where higher levels are not defined...

  • You can progress by developing related skills which are better suited to higher levels of organisational leadership.

Levels

Defined at these levels: 2 3 4 5 6

Show/hide extra descriptions and levels.

Level 1

Level 1 - Follow: Essence of the level: Performs routine tasks under close supervision, follows instructions, and requires guidance to complete their work. Learns and applies basic skills and knowledge.

Data engineering: Level 2

Level 2 - Assist: Essence of the level: Provides assistance to others, works under routine supervision, and uses their discretion to address routine problems. Actively learns through training and on-the-job experiences.

(new)

Assist in developing and implementing data pipelines and data stores.

Performs administrative tasks to provide accessibility, retrievability, security and protection of data.

Data engineering: Level 3

Level 3 - Apply: Essence of the level: Performs varied tasks, sometimes complex and non-routine, using standard methods and procedures. Works under general direction, exercises discretion, and manages own work within deadlines. Proactively enhances skills and impact in the workplace.

(new)

Follows standard approaches and established design patterns to create and implement simple data pipelines and data stores to acquire and prepare data.

Applies data engineering standards and tools to create and maintain data pipelines and extract, transform and load data.

Carries out routine data quality checks and remediation.

Data engineering: Level 4

Level 4 - Enable: Essence of the level: Performs diverse complex activities, supports and supervises others, works autonomously under general direction, and contributes expertise to deliver team objectives.

(new)

Designs, implements, and maintains complex data engineering solutions to acquire and prepare data.

Creates and maintains data pipelines to connect data within and between data stores, applications and organisations.

Carries out complex data quality checking and remediation.

Data engineering: Level 5

Level 5 - Ensure, advise: Essence of the level: Provides authoritative guidance in their field and works under broad direction. Accountable for achieving workgroup objectives and managing work from analysis to execution and evaluation.

(new)

Plans and drives the development of data engineering solutions ensuring that solutions balance functional and non-functional requirements.

Monitors application of data standards and architectures including security and compliance.

Contributes to organisational policies, standards, and guidelines for data engineering.

Data engineering: Level 6

Level 6 - Initiate, influence: Essence of the level: Has significant organisational influence, makes high-level decisions, shapes policies, demonstrates leadership, fosters organizational collaboration, and accepts accountability in key areas.

(new)

Leads the selection and development of data engineering methods, tools and techniques.

Develops organisational policies, standards, and guidelines for the development and secure operation of data services and products.

Ensures adherence to technical strategies and architectures.

Plans and leads data engineering activities for strategic, large and complex programmes.

Level 7

Level 7 - Set strategy, inspire, mobilise: Essence of the level: Operates at the highest organisational level, determines overall organisational vision and strategy, and assumes accountability for overall success.

Keywords
Small change