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Senior Data Engineer

Deriv
Dubai, UAE
Full Time
Senior
3 weeks ago
PythonSQLGCPBigQueryAirflowdbt
Free

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Why This Matters

  • Deriv’s mission is Trading for Anyone, Anywhere, Anytime. Millions of traders, around the clock, across regulatory regimes.
  • Every trade generates data. Every data point feeds analytics, compliance checks, fraud detection, and AI systems that serve customers in real time.
  • When a pipeline delivers stale data, a trader sees the wrong price. When a schema drifts undetected, a compliance report goes wrong.
  • Data engineering at Deriv isn’t back office plumbing. It’s the infrastructure that the entire business trusts.

Why Deriv

  • Natural language interfaces querying the data warehouse directly—leaders ask questions in English, answers come back in seconds.
  • Continuous KPI monitoring with anomaly detection surfacing problems before stakeholders notice.
  • Dozens of fraud detection models running against production data, continuously.
  • 400+ users on our internal workflow orchestration platform, fed by the data infrastructure you’ll help build and scale.

What You’ll Do

  • Design and build ETL/ELT pipelines across batch and real time workloads using AI assisted development—reducing build time without cutting reliability.
  • Bake in observability from the start: freshness checks, completeness monitoring, schema drift detection, lineage tracking, and alerting. Not retrofitted after launch.
  • Implement automated data quality checks and anomaly detection into every pipeline—governance built in, not bolted on.
  • Identify and resolve data issues before they surface to analysts or stakeholders.
  • Define and maintain data contracts: SLAs, SLOs, schema agreements, and producer consumer alignment.
  • Handle PII, access control, and auditability correctly in a regulated financial environment.
  • Optimise warehouse performance and cost—query efficiency, partitioning, clustering, orchestration reliability.
  • Build data models designed to scale beyond the immediate use case: dimensional modelling, semantic layers, reusable abstractions.
  • Spot gaps in the data platform and address them without waiting to be assigned.
  • Partner with analysts, product, finance, and compliance teams to translate requirements into reliable, governed data products.
  • Peer review pipeline code and push quality standards higher across the team.
  • Help onboard new engineers—share context, catch mistakes early, make others productive faster.

Who You Are

  • 6+ years in data engineering. You know that writing SQL is the easy part. The hard part is making sure data arrives on time, matches the schema you promised, and doesn’t silently break when upstream changes.
  • GCP, BigQuery, Airflow, Python—or the equivalent at comparable scale. You’ve built and maintained real pipelines across batch and streaming workloads. You’ve shipped with dbt or Dataform and understand why transformation layers matter.
  • Data modelling techniques like Kimball star schema, Data Vault, or Medallion architecture aren’t buzzwords to you—they’re tools you pick based on the problem. You understand that a pipeline without a data contract is a pipeline waiting to fail.
  • When data is wrong, you don’t patch the dashboard. You trace the problem to its source, fix it systematically, and make sure it doesn’t recur.
  • You share learnings actively, create reusable resources, and give feedback that helps others ship better code.
  • A fintech, trading, or compliance heavy background is a strong plus. You know the difference between handling PII in a textbook and handling it when auditors are checking your work.

Tech Stack

  • Cloud & Warehouse: GCP, BigQuery
  • Orchestration: Airflow
  • Languages: Python, SQL
  • Transformation: dbt / Dataform
  • Streaming: Kafka, Pub/Sub
  • Practices: CI/CD, version controlled pipelines, peer review, AI assisted development

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