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Midas

Posted 10 months ago

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Data Engineer, Platform

İstanbul, TurkeyOn-siteFull-time

AI Summary

Data Engineer responsible for owning and evolving Midas's internal data platform, from ingestion to governance, spanning batch and real-time workloads, enabling self-serve analytics for internal teams.

About this role

At Midas, we are working on real-life engineering challengesto transform the world of finance.
We’ve transformed investing in Turkey by delivering a seamless experience for everyday investors.
Today, 3.5 million users invest with Midas. Backed by an $80M Series B, the largest fintech investment ever in Turkey, we are scaling faster than ever.

At Midas, data isn’t just an input — it’s a foundation. We build products on top of it, power decisions with it, and enable every team to move faster through it. That’s why our internal data platform must be fast, reliable, secure, and self-serve by default.
As a Data Engineer, you’ll take full ownership of that platform — from ingestion to governance, from batch to real-time — and evolve it into a product that internal teams trust, build on, and rely on daily. Your work will directly accelerate product development, unlock smarter decisions, and raise the baseline for data quality across the company. This role owns the platform that powers analytics, ensuring our teams can build, iterate, and scale faster and more securely.

About Midas Team

  • We solve challenging problems and build 10x better products.
  • We expect hard work, high ownership, a strong desire to learn.
  • We bring the best people, holding high quality standards, and an environment of speed and ambition.
  • You will get to push your boundaries and learn from the best.

    • Results Expected

  • Launch a secure, multi-tenant data platform that enforces workload isolation, access control, and governance — adopted by 3+ internal teams within 6 months
  • Maintain >99% uptime across all mission-critical components of the data warehouse, storage, and processing infra, measured over rolling 90-day periods
  • Implement full observability — monitoring, alerting, and logging — with zero recurring incidents of the same type after 3 months
  • Achieve zero critical security incidents over a 6-month period by enforcing platform-wide access controls, audit logging, and secure defaults
  • Reduce manual operational load on data teams by 30%+ within 2 quarters through automation, standardization, and self-service tooling

    • Cultural Competencies

  • Takes full ownership — doesn’t wait, just solves.
  • Questions assumptions and rebuilds from first principles.
  • Balances speed and quality — ships fast, but always clean.
  • Collaborates fluidly across teams; communicates clearly, with empathy and precision.

    • Technical Competencies

  • Engineers batch and streaming pipelines that are observable, resilient, and efficient
  • Knows by heart the trade-offs between transactional, analytical, and streaming data processing — including row- vs. column-based storage formats
  • Operates confidently in Kubernetes-native environments and cloud-based data stacks
  • Writes clean, maintainable code and works fluently with Git and CI/CD workflows

    • Skills

    Access ControlAlertingAudit LoggingAutomationBatch PipelinesCI/CDCloud Data StacksData GovernanceData QualityData WarehouseGitGovernanceKubernetesLoggingMonitoringMulti-tenant ArchitectureObservabilityObservability ToolingProcessing InfraSecurity DefaultsSelf-serviceSelf-service ToolingStandardizationStorageStreaming PipelinesWorkload Isolation

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