Senior Data Analyst AI📣 Job Ad

About the Senior Data Analyst - AI Role

We are seeking a Senior Data Analyst to focus on data and analytics for our Generative AI and Recommendation Systems initiatives. This hybrid role involves owning centralized reporting to drive data-informed decisions and building the necessary data pipelines and models. You will be responsible for defining key metrics for each product, rather than relying on others for data preparation. For Recommendation Systems, a foundational understanding of Machine Learning is required to engineer appropriate features and evaluation metrics, working collaboratively with Data Scientists, ML Engineers, Product, and Backend teams.

Core Responsibilities

• Pipeline Architecture & Development: Construct and maintain scalable, fault-tolerant batch and streaming data pipelines to support analytical and ML use cases.
• Centralized Reporting & Metrics: Define critical metrics for all products and establish robust centralized reporting to surface key trends and insights.
• Data Modeling: Design and manage multi-layer data models, from staging to feature-ready marts, ensuring consistency and performance for ML models, dashboards, and APIs, with effective handling of schema changes.
• Feature Store & ML Data Flows: Engineer data flows for populating and updating the ML Feature Store, including graph data where applicable, to meet the availability and low-latency requirements of recommendation models.
• Experimentation & A/B Testing: Develop the pipelines and metric frameworks for A/B testing, including experiment schemas, assignment logging, and reliable metric computation for statistically sound results.
• ClickHouse Expertise: Serve as the domain expert for ClickHouse, focusing on schema design, performance tuning, and optimizing queries for experiment aggregation and feature serving.
• Streaming & CDC Implementation: Implement Change Data Capture (CDC) and event-driven data flows using technologies like Apache Kafka to ensure data freshness for reporting and recommendation systems.
• Orchestration & Automation: Build and manage data workflows using modern orchestration tools such as Mage AI, Airflow, or Prefect to ensure reliable data delivery and dependency management.
• ML-Aware Data Engineering: Define and interpret offline and online ranking metrics, and engineer the specific features required by ML models.
• Cross-Functional Collaboration: Partner with Data Scientists, ML Engineers, Product, and Backend teams to translate data requirements into production-ready pipelines and actionable ML features.

Required Qualifications and Experience

• Experience: 5-10 years of experience as a Data Analyst or Analytics Engineer, with a focus on building data systems for analytics and ML.
• Programming Skills: Expert proficiency in Python and advanced SQL.
• BI & Visualization: Strong skills in BI and visualization tools (*, Looker, Tableau), with a clear understanding of relevant metrics and their presentation.
• Pipelines & Orchestration: Hands-on experience building data pipelines with modern orchestration tools (*, Mage AI, Airflow, Prefect).
• Data Warehousing: Deep production experience with ClickHouse, or similar platforms like BigQuery or Snowflake.
• Data Modeling: Practical experience with multi-layer data modeling (raw, staging, marts) using methodologies such as Kimball, Data Vault, or OBT patterns.
• Experimentation Frameworks: Solid understanding of experimentation frameworks, including assignment, holdouts, metric pipelines, and variance reduction.
• ML Fundamentals: Good understanding of the ML lifecycle, how models consume data, the functionality of Feature Stores (*, Feast, Hopsworks), and large-scale feature engineering. Familiarity with ranking metrics for Recommendation Systems is also expected.

Preferred Skills

• Experience with DBT for data modeling and transformation.
• Experience building or integrating A/B testing platforms (*, Statsig, Optimizely, GrowthBook, or custom solutions).
• Familiarity with Apache Kafka and CDC tools (*, Debezium, Maxwell).
• Experience with Graph Databases (*, Dgraph, Neo4j, Amazon Neptune) and structuring data for them.
• Proficiency in JavaScript or Go.

Work Location and Type

This is a full-time position located in Makkah, Makkah Province.