Staff Analytics Engineer - Product Data Instrumentation

Salla; Jeddah; On-site; SAR 420,000 - 640,000; Full time

Job summary

Salla is seeking a Staff Analytics Engineer to own event instrumentation and behavioural data. You will own Salla's event taxonomy, tracking plans, schemas, and identity model, ensuring trustworthy validation across the engineering lifecycle.

This senior IC role requires leadership influence across engineering teams and collaboration with Product to ensure metrics trace back to deliberate, documented events. The position emphasizes scalable, maintainable analytics infrastructure and data quality.

Qualifications

• > 6 years in analytics engineering or data engineering, with 3+ years owning event instrumentation.
• > Proven track record designing an event taxonomy and tracking plan from scratch.
• > Hands-on with event collection or CDP platforms and product analytics tools.
• > Strong SQL and dbt skills; experience modelling high-volume event data in a warehouse.
• > Working knowledge of streaming architecture (Kafka or similar).

Responsibilities

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

Skills

Analytics engineering

Event instrumentation ownership

Event taxonomy design

SQL & dbt

Segment/Jitsu usage

Amplitude/Mixpanel/PostHog/GA4

Data modeling & warehouse

Cross-functional collaboration

Technical communication

Tools

Segment

Jitsu

Amplitude

Mixpanel

PostHog

GA4

dbt

ClickHouse

BigQuery

Snowflake

Kafka

Job 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.

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

• 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)