- Design, build, and maintain scalable data pipelines that ingest, transform, and deliver data for compliance analytics use cases including AML transaction monitoring, KYC/KYB, sanctions screening, and SAR reporting.
- Assess and improve existing data infrastructure: identify pipeline gaps, lineage issues, and data quality problems that silently degrade model and analytics output, and work through them systematically.
- Build and maintain compliance-specific data marts and semantic layers that allow data scientists and analysts to work independently, reducing the volume of ad-hoc data requests and increasing the team's overall throughput.
- Partner with data scientists and ML engineers to productionise feature pipelines, maintain data freshness, and build the infrastructure that keeps compliance ML models running reliably in production.
- Apply AI-assisted development as standard practice: using LLM tooling to write and review pipeline code, automate data quality checks, generate documentation, and accelerate debugging. The expectation is that you bring this fluency with you and use it to raise the quality and pace of your work.
- Implement data quality monitoring, pipeline health checks, and alerting that surfaces data integrity issues before they affect compliance decisions or model outputs.
- Work with compliance and legal teams to understand regulatory requirements around data retention, access control, and auditability, and build the controls that meet those requirements in practice.
- Support regulatory lookbacks and audit responses by ensuring historical data is retrievable, lineage is documented, and the evidence base the compliance team needs can be assembled accurately and quickly.
What We Look For In You
- 8+ years in data engineering or a closely related role, with meaningful experience in financial services, fintech, or a compliance-adjacent environment. We welcome candidates across seniority levels; scope and responsibilities will be calibrated to your experience.
- Strong Python and SQL, with hands-on experience in distributed computing frameworks such as Spark, Hadoop, or Databricks.
- Solid experience with cloud and big data platforms including Alibaba MaxCompute, Google BigQuery, AWS Redshift, or equivalent, and a track record of building production-grade pipelines where reliability and data quality are treated as requirements rather than afterthoughts.
- Hands-on fluency with AI-assisted engineering. You use LLM coding tools regularly, have applied them to real data engineering work, and have a practical view on where they improve output quality and where they need careful oversight. This is part of how the team operates, not an optional extra.
- Experience designing data marts, dimensional models, or semantic layers for consumption by non-engineering stakeholders, with an understanding of what makes a self-serve analytics layer actually usable.
- A solid grounding in data governance, access control, and audit trail requirements in regulated industries, with an appreciation for why those requirements exist and how to implement them without creating unnecessary friction.
- Good communication skills, with the ability to translate data infrastructure decisions and constraints for compliance, legal, and business stakeholders who care about outcomes rather than technical architecture.
- Familiarity with the crypto ecosystem, on-chain data structures, blockchain analytics, or VASP regulatory frameworks is a meaningful advantage for this role and will give you useful context from day one.
- Competitive total compensation package
- L&D programs and education subsidy for employees' growth and development
- Various team building programs and company events
- Wellness and meal allowances
- Comprehensive healthcare schemes for employees and dependants
- More that we love to tell you along the process!
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Skills Required
- 8+ years in data engineering or related role
- Strong Python and SQL skills
- Experience with distributed computing frameworks
- Experience with cloud and big data platforms
- Fluency with AI-assisted engineering
- Experience designing data marts and semantic layers
- Knowledge of data governance and audit trail requirements
- Good communication skills for stakeholder interaction
- Familiarity with the crypto ecosystem is a plus
OKX Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about OKX and has not been reviewed or approved by OKX.
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Fair & Transparent Compensation — Pay is considered competitive or above market, especially in engineering, product, and legal roles across major hubs. This positioning is consistently cited as a major attraction for candidates.
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Healthcare Strength — Role descriptions indicate comprehensive medical, dental, vision, life, and disability coverage, with employer-paid premiums in some cases. Health coverage is highlighted alongside core benefits like PTO and parental leave.
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Wellbeing & Lifestyle Benefits — Allowances for education and fitness, meal perks and snacks, team-building budgets, and structured learning programs are described across locations. These extras enhance the total rewards package beyond base pay.
OKX Insights
What We Do
Founded in 2017, OKX is one of the world’s leading cryptocurrency spot and derivatives exchanges. OKX innovatively adopted blockchain technology to reshape the financial ecosystem by offering some of the most diverse and sophisticated products, solutions, and trading tools on the market. Trusted by more than 20 million users in over 180 regions globally, OKX strives to provide an engaging platform that empowers every individual to explore the world of crypto. In addition to its world-class DeFi exchange, OKX serves its users with OKX Insights, a research arm that is at the cutting edge of the latest trends in the cryptocurrency industry. With its extensive range of crypto products and services, and unwavering commitment to innovation, OKX’s vision is a world of financial access backed by blockchain and the power of decentralized finance.

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