Senior Data Engineer
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About Us:
Founded in 2018, headquartered in Johannesburg, and backed by leading investors including Pantera Capital, Coinbase Ventures and Fidelity’s F-Prime Capital, VALR is a global crypto exchange offering a comprehensive suite of products—including Spot Trading, Spot Margin, Perpetual Futures, Staking, Lending, Borrowing, OTC services, VALR Invest, Crypto Bundles, and VALR Pay. Licensed by South Africa’s FSCA, with regulatory approval in Europe, VALR serves over 1.7 million registered users and 2,000 corporate and institutional clients worldwide. The exchange is dedicated to advancing a just financial future that upholds human dignity and the unity of mankind. For more information, visit valr.com.
Our Vision:
To establish VALR as a global institution that advances the economic life of human civilisation through a borderless, inclusive, and empowering financial ecosystem.
Our Mission:
To contribute towards a global financial system that upholds justice, fosters human dignity, and reflects the oneness of humanity, by serving the financial needs of individuals, communities, and institutions through innovative financial technologies.
- 4–7+ years of experience in Data Engineering or related roles, with demonstrated ownership of production data platforms.
- Proven experience taking ownership of and evolving existing data infrastructure, not just building greenfield systems.
- Deep proficiency in SQL and data modeling for analytics, including dimensional modeling and dbt.
- Strong proficiency in Python for pipeline development, automation, and tooling.
- Hands-on experience with cloud-based data platforms at scale (GCP/BigQuery strongly preferred).
- Experience designing and owning end-to-end data pipeline architectures, including orchestration (e.g., Airflow) and ELT frameworks.
- Solid understanding of data observability and data quality frameworks, and how to build data trust in an organisation.
- Familiarity with streaming or event-driven data architectures is a strong advantage.
- Strong software engineering fundamentals: version control (Git), CI/CD, infrastructure as code, and code review practices.
- Familiarity with or genuine curiosity about ML pipelines, feature engineering, and AI-assisted workflows — you do not need to be an ML engineer, but you should be comfortable operating at that boundary.
- Knowledge of data governance, privacy regulations, and secure data handling practices, particularly in a financial services context.
- Familiarity with crypto or fintech data structures and business models is a plus.
- A tertiary qualification in a technical, analytical, or quantitative field (e.g., Computer Science, Engineering, Data Science, Statistics) is preferred.
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