Looker

bi, data exploration, analytics
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Back in the dark ages before everyone decided data needed to be democratized, business intelligence meant wrestling with Excel and praying your SQL was up to snuff. Then came Looker, promising a semantic layer that would finally bridge the gap between analysts and, well, everyone else. The idea was elegantly simple: define your data relationships once and let the tool handle the rest. Quite clever, really, though one does wonder if the promise of a single source of truth ever truly materializes in any organization.

In practice, Looker’s modeling language, LookML, requires a dedicated skillset—it's not exactly point-and-click. Think of it as a beautifully crafted system that demands a devoted priesthood. While Tableau and Power BI offer broader accessibility, Looker excels in data governance and consistent metrics, especially for larger enterprises. Now under Google Cloud’s wing, it’s a solid choice for organizations willing to invest in the learning curve and maintain a robust data modeling practice – though plenty still find themselves yearning for the simplicity of a well-placed pivot table.

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analytics engineer

Senior Manager - Analytics Engineering @ comparethemarket

GB | 2025-12-26
A senior managerial role focused on transforming analytics engineering by leading a multidisciplinary team and shifting from traditional BI to scalable, self-service data solutions. The... read more »
Analytics Engineering, AI/ML, BI, Data Engineering, Analytics, Data Modelling, Data Quality, dbt, SQL, Git, DataViz, Power BI, Looker, Tableau, Agile/Scrum
analytics engineer

Senior Analytics Engineer @ entrust

GB | 2025-12-22
Entrust’s Senior Analytics Engineer role leans into the hard truth that data products beat dashboards when you’re serving a 500+ user self‑service audience across a security‑savvy business. The... read more »
Analytics, Microsoft, C, dbt, Snowflake, Looker, ETL/ELT, SQL, DataViz, BI, Tableau, Python, Git, Redshift