5+ years of professional experience as a Data Engineer or ML Engineer at a senior level
Degree in Computer Science, Data Science, or a related field from a reputable university, or equivalent demonstrable experience
AI fluency — you use AI tools actively in your daily work and know how to apply them to data problems, not just coding tasks
Strong experience designing and operating data pipelines and ETL/ELT workflows in production
Solid knowledge of data lake architecture and engineering — storage layers, cataloguing, partitioning, access patterns
Experience with AWS data services (e.g. S3, Glue, Athena, Redshift, Lake Formation)
Ability to build web services and APIs that expose data cleanly and reliably
Experience with data analysis and working alongside or directly on ML models
Strong ownership mindset — you treat the data platform as a product and take responsibility for its quality and reliability
Fluent English (written and spoken)

Nice-to-have

Familiarity with real estate or proptech data domains
Experience with Salesforce data models or CRM data integration
Hands-on ML model development and deployment experience
Exposure to agentic or LLM-powered data workflows (e.g. AI-assisted data exploration, automated anomaly detection)

Mindset

You care deeply about data quality — you know that bad data costs more than no data
Ownership-driven: you don't wait to be told what's broken, you find it and fix it
Curious about both the technical and business side — you want to understand what the data means, not just how it flows
Collaborative and communicative, comfortable working with engineers, product managers, and analysts alike

Stack: Python · SQL · AWS (S3, Glue, Athena, Redshift) · ETL/ELT · REST APIs · ML tooling · Claude · Cursor

Data Engineer - Remote - Ankara