Senior Data Engineer (Saudi National)

<div><h3>Senior Data Engineer</h3><p>Full-time | On site | Riyadh</p><p>Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money. Over 15 million users choose Tabby to stay in control of their spending and make the most out of their money.</p><p>The company's flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 40,000 global brands and small businesses, including Amazon, Noon, IKEA, and SHEIN use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores.</p><p>Tabby generates over $10 billion in annual transaction volume for its partner brands and is the highest-rated, most-reviewed, largest, and fastest-growing FinTech in the GCC region.</p><p>Tabby launched in 2019 and has since raised +$1 billion in equity and debt funding from global and regional investors, and is now valued at $4.5 billion.</p><h3>Key Responsibilities</h3><ul><li>Design, build, and maintain Tabby’s corporate data warehouse to support business users, analysts, and ML engineers.</li><li>Develop and evolve internal data services such as a Feature Store and other high-impact data products.</li><li>Build and operate robust EL/ELT/ETL pipelines for both batch and streaming use cases.</li><li>Integrate new tools and practices for data processing, storage, governance, and data quality across the platform.</li><li>Implement and maintain reliable data synchronization between internal and external systems.</li><li>Design and support high-load, scalable data processing and storage solutions, ensuring performance and reliability.</li><li>Contribute to the architecture of the data platform, including technology choices and system design decisions.</li><li>Optimize infrastructure and data workflows with a focus on cost efficiency in the cloud.</li><li>Collaborate closely with analytics, risk, and ML teams to understand data needs and deliver high-quality datasets and services.</li></ul><h3>What You’ll Bring</h3><ul><li>3–5+ years of experience as a Data Engineer, ML Engineer, or Backend Engineer working on data-intensive systems.</li><li>Proven experience in DWH development and maintenance for business users, analysts, and ML engineers.</li><li>Strong background in designing and operating high-load, scalable data processing and storage systems.</li><li>Solid understanding of data architecture patterns such as Kimball, Inmon, Medallion, and Data Mesh.</li><li>Hands‑on experience with data modeling concepts: SCD forms, normal forms, star schema, Data Vault.</li><li>Proficiency in Python following best practices for clean, testable, and maintainable code.</li><li>Advanced SQL skills and best practices for working with large datasets and complex transformations.</li><li>Familiarity with system design best practices for distributed data platforms and services.</li><li>Experience with modern data stack tools such as Airflow, dbt, BigQuery, ClickHouse, PostgreSQL, Docker, GitLab CI/CD, and Google Cloud Platform.</li><li>Experience with event‑driven systems and streaming pipelines, including tools like Debezium and message brokers/queues.</li><li>Strong communication skills in English (B2 level or higher) and the ability to work independently in a remote setup.</li></ul><h3>Nice to Have</h3><ul><li>Experience with REST and gRPC APIs as well as message brokers and queues for integrating data services.</li><li>Experience with modern systems of data storage: relational, MPP, and NoSQL databases.</li><li>Hands‑on experience with Google Cloud Platform and its data services.</li><li>GO development experience for building high-performance data services.</li></ul><h3>What We Offer</h3><ul><li>Work alongside a high-performing, international engineering team in a global fintech unicorn.</li><li>Stock options (ESOP) in a fast-scaling, pre-IPO company.</li><li>Health Insurance.</li><li>Competitive salary and other bonuses.</li></ul></div>#J-18808-Ljbffr