Data Engineer, Growth

At Midas, we are working on real-life engineering challenges to 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. Performance Marketing at Midas operates at scale — hundreds of decisions that compound daily. To move fast without breaking things, we need data infrastructure that's accurate, automated, and built for experimentation from the ground up. As an Data Engineer supporting Growth — you'll be building the systems that make marketing decisions possible. You'll own the full experimentation lifecycle, design data models that surface causality (not just correlation), and ensure every pipeline feeding Performance Marketing is monitored, tested, and bulletproof. Your work will directly influence how we allocate marketing spend, launch experiments, and scale user acquisition. 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

Achieve >99% data accuracy - measured over rolling 90-day periods - for all Performance Marketing metrics, validated through automated testing and monitoring

Build and maintain data pipelines and integrations that feed marketing attribution, cohort analysis, and ROI modeling — with zero recurring incidents that could impact spend decisions

Build and maintain data pipelines that enable rapid experimentation, reducing time-to-experiment by 50%+ within 6 months through automated data collection and analysis

Design and implement data models that empower new experiment capabilities, increasing the number of experiments launched by 25%+ within 6 months

Design and implement attribution models that enable successful attribution of conversion signals across marketing channels

Implement full observability across marketing data pipelines — monitoring, alerting, and automated anomaly detection

Technical Competencies

Builds robust, tested data pipelines using SQL, Python, and orchestration tools like Airflow (but remains tool-agnostic and adaptable)

Designs data models that support causal inference, experimentation, and marketing attribution

Understands the statistics behind A/B testing — power analysis, variance reduction, multiple testing corrections, and when to ship results

Writes clean, version-controlled code and integrates data quality checks into every pipeline

Thinks in systems — designs for monitoring, debugging, and long-term maintainability from day one

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.