Requirements
Requires 6+ years in analytics engineering, data engineering, product analytics infrastructure, or software engineering, with at least 3 years focused on event instrumentation and tracking. Must have proven experience designing event taxonomies and tracking plans from scratch, with successful adoption by engineering teams. Proficiency in event collection/CDP platforms (Segment, Jitsu), product analytics platforms (Amplitude, Mixpanel, PostHog, GA4), strong software engineering fundamentals in at least one of TypeScript/JavaScript, Kotlin, Swift, PHP, Go or Python, expert SQL and dbt, and working knowledge of streaming architecture (Kafka) are essential. Experience with server-side tagging, consent management, privacy regulation, and a clear point of view on identity resolution, sessionisation, and cross-platform stitching are also required. Excellent written communication and the ability to influence engineering teams without authority are critical.
Description
We are looking for a Staff Analytics Engineer to own event instrumentation and behavioural data at Salla. You will own Salla's event taxonomy, tracking plans, schemas, and identity model, and the validation that keeps them trustworthy. You will work inside the engineering development lifecycle, in PRDs, design reviews and pull requests, rather than downstream of it, and partner with Product so that every behavioural metric traces back to an event someone deliberately designed, documented and monitored. This is a senior individual-contributor role with company-wide leverage, suited to someone who understands that the hardest part of instrumentation is not the schema, it is getting a hundred engineers to adopt it.ResponsibilitiesOwn the design, development, and maintenance of our data models and transformation pipelinesCollaborate with cross-functional stakeholders to understand data needs and build scalable solutionsEnsure data quality and consistency through rigorous testing, validation, and monitoring practicesProactively spot and fix data issuesMaintain and document the data warehouse structure, data dictionary, and lineageDefine and enforce data modeling best practices Partner with analytics and business teams to optimize self-serve access to reliable metrics and insightsImprove developer experience across the data stack by automating workflows and simplifying data discoveryRequirements6+ years in analytics engineering, data engineering, product analytics infrastructure, or software engineering, including at least 3 years directly owning event instrumentation and trackingProven track record designing an event taxonomy and tracking plan from scratch, and driving genuine adoption across engineering teamsHands-on experience with event collection or CDP platforms (Segment, Jitsu, or similar) and product analytics platforms (Amplitude, Mixpanel, PostHog, GA4)Strong software engineering fundamentals, enough production fluency in at least one of TypeScript/JavaScript, Kotlin, Swift, PHP, Go or Python to meaningfully review an engineer's tracking pull requestExpert SQL and hands-on dbt, with experience modelling high-volume event data in a columnar warehouse (ClickHouse, BigQuery, Snowflake)Working knowledge of streaming architecture (Kafka or equivalent), including delivery semantics, idempotency, deduplication and late-arriving dataExperience with server-side tagging, consent management, and privacy regulationA clear, defensible point of view on identity resolution, sessionisation, and cross-platform stitchingDemonstrated ability to influence engineering teams without authority, and excellent written communicationNice to HaveProficiency working in ArabicExperience working in the GCCExperience in e-commerce, marketplaces, fintech, or multi-tenant SaaS platformsDepth in mobile instrumentation (native SDKs, install attribution, deep links, offline buffering)Familiarity with tracking-plan governance or event observability tooling (Avo, Segment Protocols, Trackingplan or similar)