Staff Analytics Engineer - Product Data Instrumentation

Staff Analytics Engineer – Product Data Instrumentation

Join our mission-driven team as a **Staff Analytics Engineer**, where you will architect and oversee Salla’s foundational event instrumentation and behavioral data infrastructure. This is a high-impact, senior individual-contributor role designed for a technical leader who thrives at the intersection of engineering, product, and data. You will shape the future of how we collect, model, and derive actionable insights from user behavior—ensuring every event is intentionally designed, rigorously validated, and seamlessly adopted across the organization.

In this role, you will take ownership of Salla’s event taxonomy, tracking schemas, and identity resolution models, embedding data integrity into the core engineering lifecycle. Your influence will extend beyond technical execution—you will collaborate closely with product teams to align behavioral metrics with strategic business goals, ensuring that every tracked event is purposeful, well-documented, and continuously monitored. This is not just about building pipelines; it’s about fostering a culture where data-driven decision-making is second nature.

Key Responsibilities

As the architect of Salla’s data instrumentation, your responsibilities will include:

• Design and Own Data Infrastructure: Lead the development, optimization, and maintenance of scalable data models, transformation pipelines, and event schemas that power our analytics ecosystem.
• Cross-Functional Collaboration: Partner with product, engineering, and analytics teams to define data needs, validate tracking plans, and ensure alignment between behavioral insights and business objectives.
• Data Quality Advocacy: Implement rigorous validation, testing, and monitoring frameworks to uphold data consistency, accuracy, and reliability—proactively identifying and resolving issues before they impact decision-making.
• Documentation and Governance: Maintain comprehensive documentation of the data warehouse structure, lineage, and data dictionary, while establishing and enforcing best practices for data modeling and instrumentation.
• Empower Self-Serve Analytics: Work with business teams to optimize access to reliable metrics, ensuring that insights are accessible, actionable, and derived from high-quality, well-governed data sources.
• Enhance Developer Experience: Streamline data workflows through automation, tooling, and simplification—reducing friction in data discovery and instrumentation for engineers across the organization.
• Influence Without Authority: Drive adoption of data standards and best practices by fostering collaboration, clear communication, and a shared commitment to data excellence.

This role demands both deep technical expertise and the ability to bridge gaps between technical and business stakeholders. You will be the voice of data integrity, ensuring that every event tracked is intentional, every metric meaningful, and every insight trustworthy.

Why This Matters

At Salla, we believe that great data is the backbone of innovation. As a Staff Analytics Engineer, you will play a pivotal role in shaping how we understand user behavior, optimize product experiences, and drive data-informed growth. This is an opportunity to leave a lasting impact—not just on our data infrastructure, but on the entire organization’s ability to turn insights into action.

Who You Are

We are looking for a senior engineer with:

• Proven Expertise in Data Instrumentation: At least 6 years of experience in analytics engineering, data engineering, or product analytics infrastructure, with a minimum of 3 years directly owning event instrumentation and tracking plans from conception to adoption.
• Architectural Vision: A track record of designing scalable event taxonomies and tracking plans, and the ability to drive widespread adoption across engineering teams—even without direct authority.
• Technical Proficiency: Hands-on experience with event collection platforms (e.g., Segment, Jitsu) and product analytics tools (Amplitude, Mixpanel, PostHog, GA4), along with production-level fluency in at least one of TypeScript/JavaScript, Kotlin, Swift, PHP, Go, or Python to review and refine tracking implementations.
• Data Modeling Mastery: Expertise in SQL and dbt, with experience modeling high-volume event data in columnar warehouses like ClickHouse, BigQuery, or Snowflake.
• Streaming and Privacy Awareness: Working knowledge of streaming architectures (e.g., Kafka), including idempotency, deduplication, and handling late-arriving data, as well as experience with server-side tagging, consent management, and privacy regulations.
• Identity and Session Resolution: A clear, defensible perspective on identity resolution, sessionization, and cross-platform stitching—critical for accurate behavioral tracking.
• Leadership Through Influence: Strong written communication skills and the ability to advocate for data standards, collaborate effectively, and inspire engineering teams to embrace best practices.

While not required, experience in Arabic or familiarity with the GCC market, e-commerce, marketplaces, fintech, or multi-tenant SaaS platforms will be highly valued. Similarly, depth in mobile instrumentation (native SDKs, install attribution, deep links, offline buffering) or familiarity with tracking-plan governance tools (e.g., Avo, Segment Protocols) will further strengthen your impact.

If you are a detail-oriented, collaborative leader with a passion for building robust data foundations, we’d love to hear from you.