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Job VacancyEnterprise Data Architect

Nexus Jobs Limited
Published on

£40k-45k
London, England, United Kingdom
Enterprise Data Architect As the enterprise data architect, you will own the programme pipeline for developing our data architecture strategy, including translation of our goals and objectives into enriched data dashboards. You will define and direct SXSW London's target data architecture (inc. shared data environments, data model and standards) in support of our business strategy, ensuring that data is accurate, secure and accessible to meet the needs of senior executives and department heads. Responsibilities Accountable for the data architecture & design, including implementation of company-wide data models, incorporating relevant governance frameworks, and architectural standards. Develop architectural solutions resulting in a single source of truth data lake warehouse, utilising Power Bi with built-in AI design considerations. Lead the design and development of scalable data pipelines and solutions, which support our event operations across our customer journey and channels. Collaborate with stakeholders and external technology partners to promote consistent and value driven data usage. Communicate the value of data management, through workshops and proof of concepts in partnership with business and technology partners Develop data architecture governance and standards, regarding data models and capabilities, including ability to logically model marketing and financial data. Connect disparate sources to provide seamless data access. Define KPI and Metrics for data dashboard. Map existing data sources and identity data access points. Create dedicated stakeholder UAT group for continuous output assessment. Build an executive dashboard. Configure integration and workflows. Create automation and refresh schedules. Setup training and confidence workshops. Integrating ML and AI into dashboard reporting Required Deep knowledge of modern data architecture. Experience within Cloud platforms (Azure, AWS, Databricks). Strong understanding of ETL/ELT, API's and integration patterns. Strong communication and stakeholder engagement. 5years+ in data architecture or related fields. Deep understanding of Information Security, alongside privacy and compliance regulations. Proven experience in enterprise-scale data modelling. Expertise in metadata management. Excellent analytical, planning, organisational and technical skills along with excellent written and verbal communication skills. Experience in translating complex technological requirements to an audience with minimal technical insight. This is a hybrid position based in the City of London. The position is a 6 month FTC role. The salary for this role will be circa £40K - £45K. Do send your CV to us in Word format along with your salary and availability.
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Contractor

Contractor jobExpert Monitoring & Observabilité (Datadog / Splunk) H/F

PROPULSE IT
Published on
Datadog
Monitoring
Splunk

24 months
325-650 €
Paris, France
Notre client, un grand groupe international de logistique multimodale (transport, portuaire, maritime, ferroviaire), mène un programme pluriannuel de transformation de son SI Logistique : remplacement des TMS existants par un TMS unique, digitalisation des processus opérationnels, intégration rationalisée au reste du SI. L'équipe programme, internationale, travaille en mode matriciel avec la DSI et les filiales. Dans ce cadre, nous recherchons un expert Monitoring & Observabilité pour concevoir, déployer et faire évoluer le dispositif de supervision du nouveau TMS, en intervenant dès les phases de Build pour garantir un niveau de supervision suffisant avant mise en production. Vos missions : - Définir la stratégie d'observabilité (métriques, logs, traces, indicateurs de disponibilité, performance, capacité). - Concevoir et déployer la supervision Datadog : dashboards Run/Infra/Applicatif/Management, Service Maps, monitors et alertes composites. - Concevoir et déployer la supervision Splunk : collecte et indexation des logs, dashboards, alertes de détection d'incidents. - Construire des indicateurs combinant technique et métier (volumes, taux de succès, temps de traitement). - Industrialiser l'alerting : seuils pertinents, criticité, circuits d'escalade, réduction des faux positifs. - Accompagner le passage Build → Run : dossier de supervision, documentation, formation des équipes.
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