Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.
01
Evaluation factor
Technical proficiency
35% weight
Check hands-on command of virtualization and integration stacks: Denodo or Starburst/Trino query pushdown, Informatica IDMC or Talend pipelines, Unity Catalog or Collibra lineage, Kafka streaming ingestion.
Evidence to listen for
Command of the languages, frameworks, and data tools the role actually uses
Understands correctness, performance, and failure modes, not just syntax
Has opinions on testing and can justify them
Reads and reasons about code they did not write
Five-point scoring guide
1
Poor
Cannot work independently; fundamentals are missing.
2
Needs Improvement
Weak fundamentals; output needs heavy review.
3
Satisfactory
Competent for the role; needs guidance on complex or unfamiliar work.
4
Very Good
Strong practitioner; handles hard problems with little guidance.
5
Excellent
Names specific fabric components deployed, explains pushdown optimisation and cache strategy, and cites query latency figures before and after tuning.
02
Evaluation factor
Systems and trade-offs
25% weight
Probe architecture choices: when they virtualised versus replicated, how they handled cross-source joins, semantic layer modelling, and GDPR or residency constraints across cloud and on-prem sources.
Evidence to listen for
Reasons about scale, latency, cost, and failure before writing code
Names the trade-off they chose and what they gave up
Understands the data lifecycle end to end
Anticipates what breaks at ten times the volume
Five-point scoring guide
1
Poor
No thinking beyond the immediate task; no awareness of scale or failure.
2
Needs Improvement
Limited architectural awareness; struggles with design decisions.
3
Satisfactory
Works within an existing design; makes sound local decisions.
4
Very Good
Designs for scale and maintainability; articulates trade-offs clearly.
5
Excellent
Weighs federation against materialisation with cost, freshness and governance evidence, and admits where a chosen fabric pattern later needed rework.
03
Evaluation factor
Evidence and rigour
25% weight
Test how they proved a fabric deployment worked: benchmark suites, data quality rules, reconciliation against source systems, lineage completeness audits, adoption metrics per consuming team.
Evidence to listen for
Validates results rather than trusting output
Knows how their work is measured and what a bad result looks like
Can describe a time their own analysis or model was wrong and how they caught it
Careful about data quality, leakage, and silent failure
Five-point scoring guide
1
Poor
Ships unvalidated work; no notion of how correctness is checked.
2
Needs Improvement
Validates superficially; misses obvious quality or leakage issues.
3
Satisfactory
Reasonable checks in place; rigour drops under time pressure.
4
Very Good
Validates thoroughly; can name a real error they caught in their own work.
5
Excellent
Brings measured proof: query benchmarks, reconciliation error rates, catalogue coverage percentages, and consumer adoption tracked after go-live.
04
Evaluation factor
Collaboration and communication
15% weight
Assess pre-sales and delivery interaction: running PoCs with client data teams, translating fabric concepts for stewards and CDOs, handling pushback from source system owners.
Evidence to listen for
Explains technical work to non-technical stakeholders
Gives and takes code or peer review constructively
Documents enough that the work survives their absence
Aligns with team process rather than working around it
Five-point scoring guide
1
Poor
Cannot work in a team; resistant to feedback.
2
Needs Improvement
Communication issues create rework; lone-wolf tendencies.
3
Satisfactory
Adequate team member; documentation and review participation are light.
4
Very Good
Communicates well; reliable reviewer and collaborator.
5
Excellent
Describes a PoC they scoped and demoed, names the stakeholder objections raised, and shows how architecture decisions were documented and agreed.
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