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Role
Data Architect
Level 1
Unsatisfactory
Low
Individual
Impact
Fails to define or maintain a coherent enterprise data architecture; teams operate without clear structural guidance.
Data governance framework is absent or non-functional; ownership, lineage, and quality standards are undefined.
Technology strategy decisions are made without evidence or trade-off analysis, creating costly and inconsistent platform choices.
Architectural artefacts - ADRs, target state diagrams, standards documents - are absent or out of date.
Examples
Multiple data engineering teams implemented conflicting data product patterns with no architectural guidance for a full quarter.
A significant data platform tooling change was approved without a documented trade-off analysis or total cost of ownership assessment.
Dampeners
Was appointed to a newly created role with no prior data architecture function; the starting position was effectively a blank canvas.
Significant organisational change during this period removed the stakeholder context needed to drive architectural direction.
Progression Signal
Publishes one clear enterprise data architecture standard or ADR that engineering teams can implement consistently.
Initiates a data governance forum with defined scope, accountability, and cadence.
Business Impact
Impact
Engineering teams make inconsistent architectural decisions that accumulate as technical debt and integration friction.
Data governance gaps create regulatory and compliance risk that may not be immediately visible but is compounding.
Examples
A compliance audit identified 12 data assets without defined ownership or lineage, requiring an emergency remediation programme.
Dampeners
Some governance gaps may pre-date this individual's appointment; attribution requires careful analysis.
Progression Signal
Engineering teams begin making more consistent architectural decisions; compliance risk posture improves.
Mid
Individual
Impact
Produces architectural artefacts but they lack the rigour needed for consistent implementation - ambiguous standards, underdeveloped governance frameworks.
Technology recommendations are made without sufficient evidence; the data technology radar is absent or stale.
Cross-organisational influence is limited; architecture standards are not being adopted by all data engineering teams.
Examples
Published a data mesh standard that was inconsistently interpreted across four teams due to insufficient specificity.
Data technology radar had not been updated for six months despite significant changes in the tooling landscape.
Dampeners
Developing into the full scope of a complex enterprise architecture role; rigour is expected to improve with tenure.
Progression Signal
Publishes a revised standard with sufficient specificity for consistent implementation across teams.
Updates the technology radar with current, evidence-based guidance.
Business Impact
Impact
Ambiguous architecture standards create inconsistent implementation and platform fragmentation across data teams.
Stale technology guidance leads engineering teams to make suboptimal tooling decisions.
Examples
Three teams independently adopted different orchestration approaches due to the absence of a current technology standard.
Dampeners
Business impact is architectural and accumulating; immediate delivery impact may not yet be severe.
Progression Signal
Platform fragmentation reduces; engineering teams cite the architecture guidance as useful and actionable.
High
Individual
Impact
Architecture standards are being produced but are not being adopted; influence over engineering teams is ineffective.
Data governance accountability structures are defined but not enforced; data quality and ownership remain unclear.
Resistance to feedback from engineering leadership about architectural direction is creating friction and distrust.
Examples
Published three data architecture standards in a quarter; none were adopted by the engineering teams they targeted.
Data governance forum had met monthly for six months but had made no binding decisions or enforced any standards.
Dampeners
Formal support structure and structured development plan should be in place before escalating further.
Progression Signal
At least one architectural standard is adopted and implemented consistently by a data engineering team.
Business Impact
Impact
Absence of effective architectural governance creates a fragmented data estate that is costly to maintain and evolve.
Engineering confidence in the architecture function is eroding, reducing its ability to provide strategic guidance.
Examples
Head of Engineering noted they had stopped routing architectural decisions through the data architecture review due to lack of useful guidance.
Dampeners
Business impact is structural and long-term; requires sustained attention rather than a single intervention.
Progression Signal
Engineering leadership re-engages with architecture review; architectural guidance begins to be cited in team decisions.
Level 2
Development Needed
Low
Individual
Impact
Produces enterprise data architecture guidance but with gaps in completeness - governance, compliance, and lineage requirements are underdeveloped.
Technology strategy is present but not regularly reviewed; tooling recommendations lag behind the evolving platform landscape.
Engagement with senior engineering and business leadership is limited; architectural direction is not well-socialised.
Examples
Published a target state data architecture without addressing data lineage, access control, or regulatory compliance requirements.
Technology radar had not been reviewed in a quarter despite two major tooling decisions being made in that period.
Dampeners
Developing the full breadth of enterprise architecture scope takes time; this is expected to improve with experience.
Progression Signal
Begins incorporating governance, lineage, and compliance requirements into all architectural proposals as a default.
Establishes a regular technology radar review cadence tied to engineering planning cycles.
Business Impact
Impact
Architecture gaps in governance and compliance create regulatory risk that may not surface until an audit or incident.
Lagging technology guidance leads teams to make platform decisions without adequate architectural steer.
Examples
A data platform investment was made without architectural review; it was later found to conflict with the target state architecture.
Dampeners
At this tenure level, the expectation is that these gaps are actively closing.
Progression Signal
Regulatory risk posture improves; engineering teams begin routing major technology decisions through the architecture function.
Mid
Individual
Impact
Enterprise architecture guidance is present but does not adequately address the organisation's AI and analytics ambitions.
Architecture review process exists but is inconsistently applied; some significant platform decisions bypass architectural governance.
Communication of architectural direction to executive and non-technical audiences is not yet effective.
Examples
AI/ML platform architecture requirements were not incorporated into the data architecture despite a major machine learning programme commencing.
Two significant data platform decisions in a quarter were made without architectural review due to unclear governance process.
Dampeners
AI architecture integration is a developing area; external expertise and peer network engagement may accelerate this.
Progression Signal
Begins proactively engaging with AI/ML teams to incorporate their requirements into the data architecture.
Architecture governance process becomes consistent; no significant platform decisions bypass review.
Business Impact
Impact
Data architecture misaligned with AI/ML requirements creates rework costs as the machine learning programme scales.
Architecture governance gaps allow platform decisions that conflict with the target state, increasing remediation costs.
Examples
A feature store implementation had to be redesigned six months in because data architecture requirements were not defined upfront.
Dampeners
Some of these gaps reflect organisational coordination challenges rather than individual architectural failure.
Progression Signal
AI/ML platform requirements are incorporated into the architecture; governance compliance improves.
High
Individual
Impact
Architecture guidance is produced but not adopted at the pace required; influence over the engineering organisation is developing slowly.
Data governance accountability is defined but weak; data quality and ownership standards are not being enforced consistently.
Architectural decisions in adjacent domains - application architecture, platform engineering - are not being engaged with or connected.
Examples
Data governance standards published eighteen months ago are still not adopted by two major data engineering teams.
A platform architecture decision with significant data implications was made without engagement from the data architecture function.
Dampeners
Influence and adoption at enterprise scale takes time; the pace of progress matters more than the current state alone.
Progression Signal
One previously non-compliant team adopts a data architecture standard with a clear implementation plan.
Business Impact
Impact
Slow adoption of governance standards means regulatory and quality risk continues to accumulate.
Disconnection from adjacent architecture domains creates integration and compatibility risks in the wider technical estate.
Examples
An application platform migration introduced data architecture incompatibilities because data architectural requirements were not engaged early.
Dampeners
Enterprise adoption challenges are structural; systemic intervention may be needed alongside individual development.
Progression Signal
Governance adoption rate improves; adjacent architecture integration issues begin to reduce.
Level 3
Consistently Delivers
Low
Individual
Impact
Defines and maintains a coherent enterprise data architecture - structural patterns, modelling standards, integration principles - that engineering teams implement consistently.
Operates a functional data governance framework - ownership, lineage, quality standards, cataloguing - with defined accountability across the organisation.
Maintains a current, evidence-based data technology radar that provides actionable guidance to engineering teams.
Examples
Published and socialised an enterprise data modelling standard that all four data engineering teams now follow.
Established a data governance forum with defined ownership assignments for all critical data domains within one quarter.
Dampeners
Architecture adoption is consistent within the data engineering function; broader cross-organisational influence is still developing.
Progression Signal
Architecture guidance begins to be adopted voluntarily by teams outside the data engineering function.
Business Impact
Impact
Consistent architectural standards reduce engineering variability, lower integration costs, and improve data platform reliability.
Data governance framework reduces regulatory risk and enables faster compliance responses.
Examples
Data governance framework they established enabled a GDPR subject access request to be fulfilled in one day rather than two weeks.
Dampeners
Business impact is strong within the data function; cross-organisational executive visibility is developing.
Progression Signal
Executive stakeholders begin citing the architecture function as a strategic enabler.
Mid
Individual
Impact
Leads the organisation's data architecture strategy - defining the target state, sequencing investment, and aligning engineering delivery to the long-term vision.
Connects data architecture to AI/ML and analytics ambitions, ensuring the data estate supports the organisation's strategic priorities.
Builds architectural capability across the data engineering organisation - coaching senior engineers, developing architecture review processes.
Examples
Developed a three-year data architecture roadmap aligned to the organisation's analytics strategy, adopted by the data leadership team.
Designed a feature store architecture that enabled the machine learning team to iterate at twice the previous speed.
Dampeners
Continuing to develop executive communication and cross-organisation influence to the most senior levels.
Progression Signal
Executive leadership begins citing the data architecture strategy as a key element of the organisation's data capability.
Business Impact
Impact
Data architecture roadmap provides a credible investment framework that enables multi-year platform planning.
AI/ML platform integration delivers measurable acceleration to the organisation's analytics and intelligence programmes.
Examples
The machine learning programme delivered two products in six months that previously took a year, enabled by the feature store architecture.
Dampeners
Business impact is strong and executive-visible; growing toward board-level strategic recognition.
Progression Signal
Data architecture investments they define are cited in executive and board-level strategy conversations.
High
Individual
Impact
Is the definitive technical authority for data architecture across the organisation - their decisions shape the data estate with confidence and credibility.
Drives data governance and compliance architecture that meets the organisation's regulatory requirements with engineering practicality.
Is building the next generation of data architects - coaching senior data engineers toward architectural leadership.
Examples
Defined and implemented a data lineage architecture that satisfied GDPR, financial services, and internal audit requirements simultaneously.
Developed two senior data engineers toward architectural leadership roles through structured coaching and increasing accountability.
Dampeners
Still developing the full scope of external representation and industry thought leadership characteristic of the role ceiling.
Progression Signal
Is beginning to represent the organisation at industry forums and contribute to external data architecture discourse.
Business Impact
Impact
Data governance and compliance architecture they design materially reduces the organisation's regulatory risk exposure.
Senior engineer development they drive creates a sustainable pipeline of architectural capability for the organisation.
Examples
Regulatory compliance architecture they designed received explicit positive recognition in an external audit report.
Dampeners
Business impact is strong; growing toward full strategic visibility at the most senior organisational levels.
Progression Signal
Executive and board-level stakeholders cite data architecture as a strategic organisational strength.
Level 4
Leading
Low
Individual
Impact
Defines the enterprise data architecture vision and drives its adoption across the full engineering organisation - not just the data function.
Data governance framework is authoritative and operational; data ownership, quality standards, and lineage are enforced with genuine accountability.
Technology strategy positions the organisation confidently for multi-year platform evolution, with a current and well-reasoned data technology radar.
Examples
Enterprise data architecture vision was formally endorsed by the CTO and adopted as a strategic framework across all technology teams.
Data technology radar recommendations directly shaped two major platform investment decisions, saving significant future remediation costs.
Dampeners
Full board-level data strategy influence and external industry thought leadership are developing.
Progression Signal
Is contributing to board-level data strategy conversations as a recognised technical authority.
Business Impact
Impact
Enterprise architecture vision creates a compounding platform investment framework that aligns technology choices with multi-year strategic outcomes.
Authoritative governance framework reduces regulatory risk and enables faster, more confident use of data across the organisation.
Examples
Enterprise data architecture framework they defined enabled a major acquisition integration in half the previously estimated time.
Dampeners
Business impact is strong and executive-visible; growing toward board-level strategic recognition.
Progression Signal
Board-level stakeholders cite data architecture as a strategic competitive advantage.
Mid
Individual
Impact
Is the organisation's foremost data architecture authority - shaping strategy, governing standards, and building a community of practice across data teams.
Connects data architecture to the organisation's AI, analytics, and digital ambitions, ensuring the data estate is built to enable the business's future.
Builds data architectural capability at organisational scale - architecture review processes, communities of practice, coaching programmes.
Examples
Established an organisation-wide data architecture community of practice, connecting practitioners across 12 teams.
Designed a data platform strategy that positioned the organisation to support both operational analytics and machine learning at enterprise scale.
Dampeners
Board-level strategic influence and external industry leadership are developing; not yet fully established.
Progression Signal
Board-level data strategy is shaped by this individual's architectural thinking.
Business Impact
Impact
Organisation-wide data architecture alignment creates compounding value - lower integration costs, faster capability development, stronger regulatory posture.
AI and analytics platform investments they define deliver measurable acceleration to the organisation's intelligence programmes.
Examples
Data platform strategy they authored was used as the basis for a 5-year technology investment case approved at board level.
Dampeners
Business impact is at organisation scale and board-visible; this level of impact is at the role ceiling.
Progression Signal
Is recognised externally as well as internally as a leader in enterprise data architecture.
High
Individual
Impact
Operating at or beyond the role ceiling - their architectural leadership and strategic influence are defining the organisation's long-term data capability.
Is a recognised external voice in enterprise data architecture - contributing to industry discourse, conferences, and peer networks.
Defines not just the organisation's data architecture but shapes its approach to data as a strategic asset.
Examples
Published an enterprise data strategy framework adopted as a reference model by peer organisations in the sector.
Represented the organisation at a major industry conference, presenting an architecture approach that generated significant external engagement.
Dampeners
This level of impact within a single role may indicate that a broader leadership or advisory role is the right next step.
Progression Signal
Broader organisational or industry leadership opportunity is being explored - this level of impact should not be constrained by a single role.
Business Impact
Impact
Delivering data architecture and governance value at a level that creates measurable competitive advantage for the organisation.
External recognition builds the organisation's reputation as a data engineering and architecture centre of excellence.
Examples
Named by industry analysts as an organisation leading in enterprise data architecture practices, partly attributed to this individual's published work.
Dampeners
This is the ceiling of what a Data Architect role can deliver; broader scope is the right next step.
Progression Signal
Exploration of principal architect, advisory, or broader leadership opportunities is appropriate and warranted.
Level 5
Transformative
Low
Individual
Impact
Performing well beyond the Data Architect role - their architectural vision is shaping the organisation's data strategy at the most senior levels.
Is a recognised thought leader in enterprise data architecture - influencing the discipline externally as well as internally.
Has built a data architecture function from the ground up, or transformed a failing one into a high-functioning strategic capability.
Examples
Data architecture framework they defined was adopted as a sector standard, referenced by four peer organisations.
Built the organisation's data architecture function from zero to a team of three architects with a full governance structure in 18 months.
Dampeners
Impact at this level reflects exceptional circumstances as much as exceptional performance; context matters.
Progression Signal
A broader leadership or advisory role is the appropriate next step; this level of impact should not persist without formal recognition.
Business Impact
Impact
Data architecture and governance contributions create multi-year strategic value at organisational and industry scale.
The organisation's data capability is recognised as a competitive differentiator, partly as a direct result of this individual's work.
Examples
Data strategy and architecture work they led was cited in the organisation's annual report as a key strategic capability.
Dampeners
Exceptional impact that reflects the combination of individual performance and organisational context.
Progression Signal
Broader leadership recognition - fellowship, principal architect, advisory role - is the appropriate next step.
Mid
Individual
Impact
Anomalously strong even by senior Data Architect standards - defining the discipline as well as practising it.
Their architectural frameworks and governance approaches are treated as reference models inside and outside the organisation.
Shapes the careers of multiple architects and senior data engineers, with visible compounding impact on the discipline.
Examples
Wrote and published an enterprise data governance handbook that became the standard reference for practitioners in the sector.
Developed three senior data engineers to architect level over three years through structured mentoring and progressive responsibility.
Dampeners
This level of performance is very rare; it should trigger a formal recognition and career discussion.
Progression Signal
Fellowship, principal architect, or equivalent senior technical leadership recognition is appropriate and overdue.
Business Impact
Impact
Organisation-level and industry-level data architecture contributions create compounding strategic value.
External recognition builds the organisation's reputation as a place where the data engineering discipline is defined and advanced.
Examples
External architectural frameworks they authored were cited by a regulator as a model approach for data governance in the sector.
Dampeners
Impact at this level is exceptional; it should not persist without equivalent formal recognition.
Progression Signal
Industry leadership recognition and formal seniority advancement are the right responses to this level of performance.
High
Individual
Impact
Performing at a level that transcends the Data Architect role - their contributions define the enterprise data architecture discipline.
Their governance frameworks, architectural patterns, and published thinking are used as reference standards across the industry.
Represents an extreme outlier - an architect whose impact extends far beyond any single organisation.
Examples
Authored an open-source data governance framework adopted by over 50 organisations globally.
Invited to serve on an industry standards body shaping enterprise data architecture practices.
Dampeners
This level of impact is extraordinary; the organisation's ability to retain and reward appropriately is the primary risk.
Progression Signal
Fellowship, principal architect, advisory board, or equivalent recognition is the only appropriate response.
Business Impact
Impact
The organisation benefits from being associated with this individual's work - attracting talent, building reputation, and influencing strategy.
Their contributions create value that extends well beyond the organisation to the broader data engineering ecosystem.
Examples
The organisation's data architecture programme, led by this individual, was cited by analysts as an industry-leading case study.
Dampeners
Retaining this individual requires commensurate recognition; failure to act is a significant retention risk.
Progression Signal
Formal recognition at the highest available level is the only appropriate response to this level of contribution.