À propos de ce poste Senior Data Engineer – Digital & Behavioural Telemetry chez Cartrawler
What you will do as a Senior Data Engineer:
Digital & Behavioural Telemetry Data Engineering: Shapes the unified behavioural data models that connect customer actions, journey stages, product interactions and technical telemetry, enabling consistent analysis of how users move through digital experiences across partners, products and channels. Integrate web-engine telemetry, real user monitoring and related event data so that behavioural patterns, friction points and conversion opportunities can be understood reliably.
Instrumentation, Tagging & Event Contracts: Partner with P&T engineering teams to define how product and web events are tagged, named, contextualised and versioned. Establish reusable event taxonomies, identifiers, metadata and testable contracts so new features and journeys produce reliable data. Evolve the digital behavioural data implementation, including development and debugging capability.
Conversion Performance & Digital Journey Data Products: Engineer and evolve governed data products that measure performance across key digital journeys and acquisition and revenue funnels. Provide the behavioural data foundations required to measure session and search activity, availability, funnel progression, booking conversion, ancillary and revenue outcomes, and agreed attribution measures.
Data Enablement & Analytics Enablement: Turn product, engineering and business data needs into reusable, governed data structures that can be consumed safely downstream. Contribute event definitions, technical context, lineage and KPI guidance to the central definitions repository, using documentation-as-code and Markdown for business and metric definitions.
Observability Engineering: Connect behavioural and customer-journey data with real user monitoring and relevant operational telemetry so teams across CT can understand how technical performance influences customer experience, conversion and journey progression.
Quality, Security & Lifecycle: Set and implement expectations for data quality at creation, automated testing, breaking-change controls, ownership, classification, access, privacy, retention and handling of sensitive data. Ensure critical telemetry and conversion data products are monitored, documented, discoverable and safe to evolve.
Partner, Analyst & Product Enablement: Act as the senior technical SME for analysts, P&T teams and partner questions relating to telemetry, tagging and digital behavioural data. Maintain a digital measurement and data roadmap that identifies the data capability required to quantify behavioural friction, conversion performance, technical performance and website or product experience opportunities.
What you’ll bring to the team:
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5-7+ years' experience in data engineering, digital analytics engineering, product telemetry or a related technical role, with evidence of senior ownership across production data products and cross-team delivery.
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Strong hands-on experience engineering digital behavioural or telemetry data in a production environment, using an event collection platform such as Snowplow, Adobe Experience Platform , Google Analytics or a comparable technology.
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Practical experience with event tracking and telemetry concepts such as schemas, enrichments, event contexts, processing pipelines and warehouse data models, including local development, debugging and testing approaches.
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Advanced SQL and strong Python skills, with hands-on experience using modern cloud data platforms and transformation tooling; such as Snowflake, dbt , AWS or similar technology stack.
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Experience designing event taxonomies, schemas, data contracts, versioning and metadata for web or product telemetry, including semi-structured JSON data.
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Strong understanding of digital analytics and conversion measurement, including behavioural funnels, search and booking progression, landing and entry-point performance, attribution, journey progression and behavioural KPIs.
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Experience modelling high-volume event data into reusable facts, dimensions and data products that support both detailed investigation and governed business reporting.
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Understanding of RUM(real user monitoring) and observability concepts including metrics, logs, traces, correlation, instrumentation and the relationship between technical performance and customer experience.
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Experience implementing data quality, automated testing, schema-change controls, privacy, classification, access, retention and lifecycle practices for telemetry or behavioural data.
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Strong stakeholder and partner communication skills, with the ability to explain complex event and telemetry data to analysts, engineers, product teams and non-technical consumers.
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Working knowledge of Git, CI/CD, automated testing and documentation practices, with a track record of improving engineering standards and enabling others to work independently.
