Senior Data Analyst (Hardware Automation)
On-siteAmsterdam, North Holland, The Netherlands
Job Summary
Lead end-to-end analytical projects independently, defining problems, building Python and SQL pipelines, and driving stakeholder adoption. Build and maintain reliable data pipelines while designing dashboards that provide visibility into fleet health, utilization, and automation coverage. Analyze large-scale hardware telemetry to identify bottlenecks and translate complex signals into actionable recommendations for infrastructure scaling. Collaborate with SWE, SRE, and operations teams to quantify automation impact and inform prioritization decisions. Raise team standards through documentation, metric definitions, and mentoring.
Required Qualifications
- Significant experience as a Data Analyst, Senior Data Analyst, or in a similar role with strong technical ownership
- Strong proficiency in Python and SQL — you write clean, production-quality code, not just scripts
- Proven experience building and maintaining dashboards used by engineering or operations teams
- Experience owning analytical projects end-to-end: from data modelling and pipeline development through to stakeholder delivery
- Solid grounding in statistics and analytical thinking, including descriptive analytics, hypothesis testing, and regression fundamentals
- Strong attention to data quality, including validating definitions, identifying inconsistencies, and implementing monitoring
- Comfort working with large, complex, and sometimes ambiguous datasets — including telemetry, logs, or operational data
- Ability to communicate technical findings clearly to non-technical audiences, including senior leadership
- Strong problem-solving skills — you break down ambiguous questions, form hypotheses, and identify practical next steps independently
- Working knowledge of spoken and written English
- Applicants must be authorized to work in the country in which they apply
Desired Qualifications
- Experience with hardware infrastructure, data centre operations, or cloud infrastructure analytics
- Familiarity with modern data stacks such as dbt, Airflow, BigQuery, Snowflake, or PostgreSQL
- Experience with BI tools such as Tableau, Power BI, Looker, or Superset
- Background in automation analytics, capacity planning, or fleet management
- Experience mentoring other analysts or contributing to team standards and documentation
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