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
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