Lead Analytics Engineer (Ic5)

RequirementsInscríbase ahora, lea los detalles del trabajo desplazándose hacia abajo.Verifique que posee las habilidades necesarias antes de enviar una solicitud.You have significant experience in software engineering, data engineering, analytics engineering, or data platform engineering, with a strong track record of delivering complex technical projects in productionYou have already operated as a Tech Lead, Staff Engineer, Senior Engineer with strong leadership responsibilities, or Engineering Team Lead.You are comfortable guiding engineers, making architecture decisions, and creating alignment across technical and non-technical stakeholdersYou have experience working closely with Product Managers or Data Product Managers, and you understand how to turn ambiguous business goals into pragmatic technical plansExperience in B2B SaaS, fintech, or regulated environments is a plus, but not requiredModern data platforms, including warehouses, transformation layers, BI, semantic layers, and observabilityData modeling, data quality, governance, documentation, and metric consistencyBackend or platform engineering, ideally with TypeScript, Node.js, event-driven systems, APIs, or cloud infrastructureDbt, Snowflake, SQL, CI/CD, GitHub workflows, testing, and production ownershipTracking systems, event collection, or data contractsAI-enabled tooling or a strong interest in using AI to improve data access and engineering deliveryYou do not need to be equally deep in backend, data engineering, and analytics engineering, but you should be able to reason across these domains, ask the right questions, and guide specialists toward coherent technical decisionsYou are hands?on, pragmatic, and outcome?driven.You care about clean architecture and strong engineering standards, but you know how to sequence work and avoid over?engineeringYou are a strong communicator who can explain technical topics clearly to engineers, product stakeholders, and business teams.You are comfortable navigating ambiguity, making trade?offs, and creating clarity for othersYou enjoy mentoring engineers and helping teams improve the way they work.You lead by example, with curiosity, kindness, ownership, and a bias for actionYou are fluent in written and spoken English, our business languageWhat the job involvesAs Tech Lead Core Data, you will be the technical and delivery anchor of the squadYou will partner closely with the Data Product Manager to shape the squad roadmap, translate strategic data initiatives into executable plans, and ensure the team delivers high?impact outcomes on timeWhile the PM will remain the main owner of external stakeholder communication and discovery, you will drive the squad’s internal operating rhythm: planning, refinements, technical breakdown, delivery follow?up, rituals, and continuous improvementYou will also work very closely with the Head of Data to align the squad’s technical roadmap with Spendesk’s broader data strategyOver the next 12 months, your main challenges will include:Leading the complete redesign of Spendesk’s core data model to create a clean, scalable, trusted foundationSupporting the migration to a new BI tool and the rationalization of existing dashboards and reporting assetsImproving data quality, observability, documentation, and governance across the platformHelping implement AI?powered tooling to make data easier to access and use across the companyDriving the full revamp of tracking and event collection in collaboration with product and engineering squadsImproving the squad’s delivery practices, including better planning, clearer ownership, and the use of AI to accelerate executionSupporting recruitment, onboarding, and the growth of engineers in the squadYou will define and drive the technical direction of the Core Data squad.This includes shaping the architecture of our data platform, from ingestion and tracking to transformation, semantic modeling, BI, and data exposureYou will lead design discussions for new pipelines, models, services, tracking systems, and integrations.You will ensure that the squad makes pragmatic, scalable, and cost?effective technical decisions, with clear trade?offs between speed, reliability, governance, security, and long?term maintainabilityYou will remain close to implementation: writing or reviewing code, dbt models, infrastructure changes, technical designs, and helping debug complex issues when needed.You will be expected to raise the quality bar across software engineering, data engineering, and analytics engineering practicesYou will help rebuild Spendesk’s core data model into a clean, consistent, and trusted foundation for analytics, product insights, operational reporting, and AI use casesYou will drive standards around data modeling, naming conventions, ownership, contracts, documentation, and testing.xqbhyrx You will help ensure critical datasets have clear SLAs or SLOs, proper observability, and well?defined incident or escalation processes where neededYou will work closely with Analytics Engineers, the Data Engineer, the Software Engineer, and domain teams to reduce duplication, prevent metric fragmentation, and make shared data assets easier to discover, understand, and reuseYou will act as the main technical reference for the squad.Externally, you will support the PM in communicating roadmap decisions, dependencies, risks, and delivery progress when technical clarity is needed#J-*****-Ljbffr

Verifique que posee las habilidades necesarias antes de enviar una solicitud.You have significant experience in software engineering, data engineering, analytics engineering, or data platform engineering, with a strong track record of delivering complex technical projects in productionYou have already operated as a Tech Lead, Staff Engineer, Senior Engineer with strong leadership responsibilities, or Engineering Team Lead. You are comfortable guiding engineers, making architecture decisions, and creating alignment across technical and non-technical stakeholdersYou have experience working closely with Product Managers or Data Product Managers, and you understand how to turn ambiguous business goals into pragmatic technical plansExperience in B2B SaaS, fintech, or regulated environments is a plus, but not requiredModern data platforms, including warehouses, transformation layers, BI, semantic layers, and observabilityData modeling, data quality, governance, documentation, and metric consistencyBackend or platform engineering, ideally with TypeScript, Node.js, event-driven systems, APIs, or cloud infrastructureDbt, Snowflake, SQL, CI/CD, GitHub workflows, testing, and production ownershipTracking systems, event collection, or data contractsAI-enabled tooling or a strong interest in using AI to improve data access and engineering deliveryYou do not need to be equally deep in backend, data engineering, and analytics engineering, but you should be able to reason across these domains, ask the right questions, and guide specialists toward coherent technical decisionsYou are hands?on, pragmatic, and outcome?driven. You care about clean architecture and strong engineering standards, but you know how to sequence work and avoid over?engineeringYou are a strong communicator who can explain technical topics clearly to engineers, product stakeholders, and business teams. You are comfortable navigating ambiguity, making trade?offs, and creating clarity for othersYou enjoy mentoring engineers and helping teams improve the way they work.