6 days ago

Data and Automation Systems Builder

Jobgether

Netherlands

6 days ago

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A partner company is seeking a Data and Automation Systems Builder based in the Netherlands to design and build data pipelines, dashboards, alerts, and automated workflows. The role requires strong SQL, cloud data warehouse, BI, and workflow automation skills, plus a builder mindset and heavy use of AI tools. It is a full-time, on-site position with an exclusive independent contractor engagement.

AI-enabledOn-siteFull-timeEntry LevelSQLBigQuery

Data and Automation Systems Builder

Apply

AI-enabledOn-siteFull-timeEntry LevelSQL

Salary

Not specified

Work Location

Netherlands, NL

Work Model

On-site

Employment Type

Full-time

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)

SQLBigQueryLooker Studion8nMakeAI toolsData pipelinesDashboardsWorkflow automationCloud data warehousesBI platformsScripting

Soft Skills

Problem-solvingLogical reasoningAnalytical skillsOwnershipIndependenceCommunicationCollaborationAdaptability

Preferred Qualifications

Technical (Nice-to-have)

AI agentsLLM APIsNatural-language interfaces

Key Responsibilities

•Contribute to the development of an AI-powered data engine that enables natural-language data queries and supports automated operational decision-making.
•Design and build automated data pipelines, dashboards, and reporting systems using BI platforms such as Looker Studio or equivalent tools.
•Translate loosely defined business requirements into functional, end-to-end technical solutions without relying on detailed specifications.
•Build real-time alerts and automated triggers that identify process failures, deviations, bottlenecks, and operational risks.
•Surface stage-by-stage process events and timestamps across core platforms to identify where workflows slow down or become blocked.
•Develop and maintain workflow automations connecting raw data sources with reporting, monitoring, and alerting systems using tools such as n8n, Make, or custom scripts.
•Investigate and resolve data quality, integrity, and pipeline issues directly at their source.
•Use modern AI tools as a core part of the development workflow to accelerate research, coding, prototyping, debugging, and system development.
•Partner closely with engineering, automation, and business stakeholders to understand requirements and deliver practical solutions.
•Create lightweight, accessible documentation that enables non-technical managers to understand and use the systems independently.
•Continuously improve the reliability, scalability, and usability of the organization's data and automation ecosystem.
•Take ownership of projects from initial problem definition through development, deployment, troubleshooting, and ongoing improvement.

DataAutomationAISQLBigQueryLooker Studion8nMakeFull-timeOn-site

Key Responsibilities

•Contribute to the development of an AI-powered data engine that enables natural-language data queries and supports automated operational decision-making.

•Design and build automated data pipelines, dashboards, and reporting systems using BI platforms such as Looker Studio or equivalent tools.

•Translate loosely defined business requirements into functional, end-to-end technical solutions without relying on detailed specifications.

•Build real-time alerts and automated triggers that identify process failures, deviations, bottlenecks, and operational risks.

•Surface stage-by-stage process events and timestamps across core platforms to identify where workflows slow down or become blocked.

•Develop and maintain workflow automations connecting raw data sources with reporting, monitoring, and alerting systems using tools such as n8n, Make, or custom scripts.

•Investigate and resolve data quality, integrity, and pipeline issues directly at their source.

•Use modern AI tools as a core part of the development workflow to accelerate research, coding, prototyping, debugging, and system development.

•Partner closely with engineering, automation, and business stakeholders to understand requirements and deliver practical solutions.

•Create lightweight, accessible documentation that enables non-technical managers to understand and use the systems independently.

•Continuously improve the reliability, scalability, and usability of the organization's data and automation ecosystem.

•Take ownership of projects from initial problem definition through development, deployment, troubleshooting, and ongoing improvement.