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.

Responsibilities

• Own the design, development, and maintenance of our data models and transformation pipelines
• Collaborate with cross-functional stakeholders to understand data needs and build scalable solutions
• Ensure data quality and consistency through rigorous testing, validation, and monitoring practices
• Proactively spot and fix data issues
• Maintain and document the data warehouse structure, data dictionary, and lineage
• Define and enforce data modeling best practices
• Partner with analytics and business teams to optimize self-serve access to reliable metrics and insights
• Improve developer experience across the data stack by automating workflows and simplifying data discovery

Desired Candidate Profile

6+ years in analytics engineering, data engineering, product analytics infrastructure, or software engineering, including at least 3 years directly owning event instrumentation and tracking.

Proven track record designing an event taxonomy and tracking plan from scratch, and driving genuine adoption across engineering teams

Hands-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 request.

Expert 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 data

Experience with server-side tagging, consent management, and privacy regulation.

A clear, defensible point of view on identity resolution, sessionisation, and cross-platform stitching.

Demonstrated ability to influence engineering teams without authority, and excellent written communication.

Nice to Have

• Proficiency working in Arabic
• Experience working in the GCC
• Experience in e-commerce, marketplaces, fintech, or multi-tenant SaaS platforms
• Depth 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)