Asset Data Engineer
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Asset Data Engineer
Permanent
Reading - 2 days/week hybrid
Turn infrastructure data into insight. Turn insight into better decisions.
The Asset Data Engineer plays a critical role in improving the reliability, efficiency, and value of infrastructure assets. Sitting at the intersection of data, operations, and asset management, this role provides the evidence base that underpins performance improvement, risk management, regulatory assurance, and investment decisions.
You’ll translate complex operational and asset data into clear, trusted insight that helps leaders understand how the infrastructure is performing today—and where to intervene to improve outcomes tomorrow.
Why this role matters
Infrastructure performance is only as good as the insight behind it. This role ensures decisions are grounded in trusted data, robust analysis, and clear accountability. By providing clarity on performance, risk, and value, the Infrastructure Performance Analyst enables smarter maintenance, targeted investment, and sustained service excellence—today and in the long term. This is a hybrid role with a minimum of 2 days per week in our Central Reading office.
What you’ll be here to do:
You’ll own the performance insight that drives smarter asset and operational decisions. You’ll:
Performance Measurement & Insight
- Define, track, and continuously refine KPIs and KRIs covering asset health, reliability, availability, safety, cost, and service performance.
- Build dashboards and reports that turn complex datasets into actionable insight for both operational teams and senior leaders.
- Conduct trend, variance, and root-cause analysis, quantifying impacts on cost, risk, and customer/service outcomes.
- Benchmark performance against internal targets and external peer or industry standards where available.
Data Management & Analytics
- Source, cleanse, and integrate data from asset systems (EAM/CMMS), telemetry/SCADA, IoT, and finance/operations platforms.
- Develop repeatable analytical pipelines, including ETL processes, data quality checks, and reconciliations.
- Maintain data dictionaries, metric definitions, and lineage to ensure consistency and trust in reporting.
- Apply statistical and analytical techniques (forecasting, reliability modelling, segmentation) to identify performance drivers and emerging risks.
Asset & Reliability Engineering Support
- Partner with Asset Management and Operations teams to assess maintenance strategies, failure modes, and lifecycle cost impacts.
- Support reliability programmes, including MTBF/MTTR analysis, availability modelling, and condition-based maintenance.
- Provide robust evidence to support investment prioritisation, optimisation (TOTEX / whole-life), and operational interventions.
Performance Governance & Assurance
- Support the performance framework, including definitions, targets, thresholds, tolerances, and escalation mechanisms.
- Prepare performance packs for monthly and quarterly reviews, audit committees, and regulatory or shareholder submissions.
- Provide independent challenge and assurance to reported figures, assumptions, and analytical methods.
Continuous Improvement & Innovation
- Identify opportunities to automate reporting, improve data quality, and standardise performance metrics.
- Pilot and scale new analytical approaches, including anomaly detection, predictive maintenance, and advanced reliability techniques.
- Document methodologies, manage version control, and embed best practice across the performance function.
Who we’re looking for:
You’re a curious, structured thinker who enjoys making sense of complex systems and influencing decisions through evidence. You’ll have:
- Proven experience in performance analysis within infrastructure, operations, or asset-intensive environments.
- Strong data skills: Excel, SQL, and at least one BI/analytics tool (Power BI preferred).
- Solid grounding in statistics, time-series analysis, and building clear, reliable dashboards and reports.
- Understanding of asset management principles, including maintenance strategies, reliability, and lifecycle costs.
- Ability to translate analysis into practical recommendations for operational and senior stakeholders.
If you also have the following, we’re especially interested in talking to you:
- Experience with EAM/CMMS platforms (e.g. Maximo, SAP PM).
- Exposure to telemetry/SCADA or IoT data.
- Familiarity with ISO 55000 and performance governance frameworks.
- Experience with predictive maintenance, anomaly detection, or reliability modelling.
- Background in regulated sectors (telecoms, energy, water, transport).
- Professional certifications:
- Data/BI (e.g. Microsoft Power BI Data Analyst)
- Reliability/Asset Management (e.g. IAM Certificate, CMRP)
- Process Improvement (e.g. Lean Six Sigma)