Job closedPosted a month ago

SiFi - Data Analyst

Data Analyst
Open to offers Riyadh, Saudi Arabia
Twine JobsVerified
Stretford, United Kingdom · Organization
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Data Analyst is needed in Riyadh, Saudi Arabia.

Client: SiFi

Location: Riyadh(remote), 01, sa

Contract: Freelance

Job Description

This is a remote position.

SiFi is a B2B spend management platform operating under SAMA regulation. We move fast and we decide with data, which means someone has to build the reporting layer everyone relies on and then go digging when the numbers look wrong.

This role does both. You will own the dashboards that the business runs on, and you will be the person who takes an ambiguous question and comes back with an answer people can act on.

Requirements

What we’re looking for

Required:

  • Strong SQL. You can write and debug complex joins, window functions, and CTEs against a large transactional schema without hand-holding.
  • Experience building dashboards in a BI tool (Metabase, Power BI, Tableau, Looker, or similar).
  • Python or R for analysis beyond what SQL handles cleanly.
  • Ability to scope a vague business question into something answerable, and to say clearly when the data can’t answer it.
  • Comfortable working directly with ops, product, and commercial stakeholders.

Nice to have:

  • Fintech, payments, or banking background. Familiarity with card transaction data, authorisation flows, or scheme reporting is a strong advantage.
  • Exposure to KSA financial services and SAMA reporting requirements.
  • Workflow automation experience (n8n, Airflow, or similar).

Additional Information

  • Build and maintain dashboards across spend, card operations, support, and GTM. Own them end to end: definitions, data quality, refresh reliability.
  • Write SQL directly against our core banking database and other production sources. Most of the interesting work starts here.
  • Run deep dives on demand: decline code patterns, cohort behaviour, funnel drop-offs, campaign performance, anomalies flagged by ops.
  • Turn findings into decisions. A clear recommendation with a stated confidence level beats a beautiful chart with no conclusion.
  • Define and document metrics so the same number means the same thing across teams.
  • Support regulatory and internal reporting where analytics is the input.
  • Automate the repetitive parts. If you’re pulling the same extract every week, build it once and stop.

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