Dashboard
Open jobs
1898
Companies looking for
1786
Once upon a time, decision-makers were drowning in reports. Then came the dashboard, promising salvation in the form of beautifully rendered KPIs and instantly digestible insights. The idea? Consolidate everything onto a single screen, transforming raw data into actionable intelligence. Quite clever, really, though one does wonder if most dashboards end up resembling digital magpie nests – crammed with metrics nobody actually uses but feels obligated to display.
In practice, building a truly useful dashboard is less about technology and more about ruthless prioritization. Too often, they become the lovechild of Excel and PowerPoint, visually appealing but functionally limited. While alternatives like detailed reports and ad-hoc analysis offer deeper dives, dashboards excel at monitoring key trends. Today, they’re ubiquitous – from C-suite overviews to operational monitoring – though the signal-to-noise ratio remains a constant battle. Everyone has one, but few are truly happy with it.
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Jobs (this month)
1898
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1786
Jobs in using Dashboard for but please no
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data engineer
Senior Software Engineer, Data Infrastructure (RDBMS) @ trmlabs
US | 2025-12-28
| USD
200000 - 220000
/ year
This role at TRM Labs is a high-impact, mission-driven position that demands deep expertise in data engineering, blockchain, and infrastructure. The job requires experience with production-grade...
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Blockchain, Analytics, Data Science, Data Streaming, SQL, Data Engineering, RDBMS, PostgreSQL, MySQL, SQL Server, Airflow, dbt, Funnel, Dashboard | ||
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data engineer
Product Manager, Data Foundations @ stripe
US | 2025-12-25
| USD
214300 - 321500
/ year
Stripe’s Data Foundations PM role entices you as a founding member of the product discipline, tasked with shaping data movement, storage, governance, and AI-enabled data products for Stripe’s...
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Data Quality, AI/ML, Dashboard, C, RAG, Analytics, Data Governance, Airflow, Spark, Flink, Iceberg, Trino, dbt, Management, AWS Lambda, Go, DuckDB | ||
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promoted
O'Reilly: Building AI Agents with Model Context Protocol (MCP)Design and implement composable agent architectures using MCP. Understand the MCP architecture and how it enables AI applications to access external context. Build MCP servers that expose tools, resources, and prompts to LLMs. |
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data engineer
Data Engineer – Analytics & ETL @ talent-software-services
US | 2025-12-23
A hands-on Data Engineer – Analytics & ETL in Mountain View, tasked with onboarding data streams, building scalable ETL pipelines in Azure Data Factory and Logic Apps, migrating estates to Fabric,...
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Analytics, ETL/ELT, Data Streaming, Dashboard, Fabric, Azure, ADF, Data Modelling, SQL, Power BI, Data Engineering, Splunk, Python, Bash, DataViz, Grafana, Data Governance, Cloud Computing, Microsoft |
