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Data Engineer Payments & Funds-Flow

Data Engineer Payments & Funds-Flow

OSL
8-10 Years
Early Applicant
  • Posted a day ago
  • Be among the first 10 applicants

Job Description

About the Role

OSL Group is a listed digital-asset and fintech group; Banxa is our regulated crypto payments and fiat on/off-ramp business. This role is the data owner for the payments and funds-flow domain, serving the payments, finance, compliance and risk teams. Core stack is MaxCompute and DataWorks with CDC-based ingestion. The role works in an AI-native way by default.

What We're Really Looking For

We care more about how you think and the leverage you create than about any specific tool.

  • Modelling judgement. You turn messy, multi-source payment flows into clean, reusable models, and can defend your choices on grain, dimensions and trade-offs. You've owned at least one subject area end to end.
  • Correctness under compliance. You treat financial data as something that must reconcile and survive audit — idempotent, precise, verifiable — not just loaded.
  • Ownership over ambiguity. You engage upstream at product kick-off, pin down definitions before writing code, and stay accountable from ingestion to the business outcome rather than stopping at your layer.
  • Influence without authority. You get backend, SRE, finance and compliance teams to move with you, and you set the quality bar and SLAs for a domain rather than following someone else's.
  • AI-native leverage. You use AI agents/LLMs as a core part of how you build, review and operate data — automating the repetitive, accelerating the hard, and building data agents and copilots that raise the whole team's throughput. You have a point of view on where AI helps and where it must not be trusted.

Must-Have

  • 8+ years in data engineering or data warehousing, including 2+ years in payments, settlement, financial services or exchange environments.
  • Strong SQL and dimensional modelling, with end-to-end ownership of at least one subject area.
  • Production CDC ingestion experience, including late and out-of-order events, deduplication, soft deletes and schema evolution.
  • Accuracy engineering for financial data: idempotent writes, numeric precision, reconciliation and cross-system consistency checks.
  • Agent-based development capability: multi-step agent workflows, tool and data-source integration through MCP, and reusable skills; context engineering, tool-call design, agent evaluation and debugging.
  • Ownership of a data quality framework, covering rule design, threshold rationale, alert response and SLA commitments.

Preferred

  • Crypto or digital-asset data experience: on/off-ramp, on-chain or stablecoin settlement, multi-asset exposure.
  • Multi-timezone, multi-currency and multi-region data, including business-day cut-off, FX treatment and localisation.
  • Financial audit or regulatory-reporting support, including source-of-truth and explainable change history.
  • Cross-engine migration experience, for example MaxCompute or Hadoop to Snowflake or Databricks.
  • Building metadata, lineage, catalogue, metric platforms — or AI data agents / LLM-powered tooling.
  • Python or Java for internal tooling and services.
  • Familiarity with compliance constraints on architecture: PCI DSS, GDPR, data localisation, row and column level security, masking.

How We Work

  • Definitional rigour — clarify before you code.
  • Reproducible by default — idempotent, re-runnable, verifiable.
  • End-to-end ownership — own the full chain and faces the business directly.
  • AI-native — highest-leverage path first; automate the routine, keep human judgement where correctness and compliance demand it.

More Info

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Key Skills

Agent-based development capability

dimensional modelling

Accuracy engineering for financial data

Production CDC ingestion

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