Staff Data Engineer, Finance Data Platform

Domain Architecture & Technical Direction

• Own the end-to-end Finance data architecture: from ODS ingestion through CDM transformation to reporting mart, with clear data lineage documented at every layer
• Define and enforce data modelling standards for Finance: period cut-off immutability, multi-entity consolidation logic, revenue recognition alignment, and audit trail completeness
• Lead the design of scalable pipelines supporting trading data, asset positions, P&L, and cost accounting across multiple legal entities and jurisdictions (SG, EU, US, and others)
• Make architectural decisions independently and articulate trade-offs clearly to both engineering peers and non-technical Finance stakeholders

Financial Reporting & Audit Readiness

• Partner with Accounting, Finance PMO, and Treasury to deliver datasets for month-end close, statutory reporting, and board-level financials on time and to audit standard
• Ensure every financial figure is traceable back to the source system with full transformation history — no black boxes
• Build the data foundation that supports OKX's regulatory reporting obligations and long-term financial reporting maturity

Data Quality & Controls

• Design proactive, self-validating DQC frameworks — reconciliation logic, SLA monitoring, and anomaly detection built into pipelines, not bolted on after incidents
• Own incident response for Finance-critical pipeline failures; conduct structured post-mortems and drive permanent fixes
• Define "done" for financial correctness in partnership with Accounting; hold the line on data quality standards even under delivery pressure

AI-Native Finance Data

• Lead the team's adoption of AI-assisted engineering: LLM-assisted development, automated anomaly detection, intelligent reconciliation, AI-generated reporting summaries
• Evaluate and introduce AI tooling into Finance data workflows with production evidence — not POC demos
• Set the bar for what an AI-native Finance data team looks like, and bring junior engineers along

Technical Leadership & Influence

• Be the go-to escalation point for Finance data domain questions across the team
• Mentor and grow engineers working in the Finance domain; translate domain complexity into learnable patterns
• Represent Finance Data in cross-team architecture discussions, sprint planning, and stakeholder reviews
• Document domain knowledge that outlasts any individual — data dictionaries, pipeline specs, onboarding guides

• 6+ years in data engineering, with at least 3 years owning a Finance, Accounting, or financial reporting data domain end-to-end
• Deep understanding of financial data fundamentals: period close and cut-off rules, revenue recognition, multi-entity consolidation, reconciliation, and audit trail requirements
• Demonstrated experience building data systems that have been reviewed in a statutory audit or regulatory review
• Strong SQL and Python; proven ability to design and maintain complex production pipelines at scale
• Experience designing for immutability and lineage — financial data that can be rolled back, re-run, and traced without manual intervention
• Track record of operating with significant autonomy: defining requirements from ambiguous stakeholder input, not just executing tickets

• Experience at a crypto exchange, fintech, or company that has gone through IPO preparation or public company financial reporting
• Familiarity with regulatory reporting requirements across multiple jurisdictions (MAS SG, SEC, FCA, or equivalent)
• AI/LLM tooling applied to data engineering workflows in production — concrete examples required; "exploring" does not count
• Experience with Spark, Airflow, or equivalent orchestration at scale
• Prior experience as a de facto domain lead or tech lead without formal people management title
• Background working with Accounting/Controllership teams as a technical counterpart