[Hiring] Data Engineer @Properti

Role Description

As our Data Engineer, you'll own the data platform that powers properti's products, analytics, and AI systems. You'll design and operate the pipelines that bring data in, the infrastructure that stores and organizes it, and the services that make it accessible — all with a high standard of reliability and ownership. This role sits at the intersection of data engineering, analytics, and machine learning. You won't just move data — you'll make sense of it, expose it, and use it to generate real business insight.

Data Platform & Pipelines

• Design, build, and maintain ETL/ELT pipelines that ingest, transform, and deliver data from internal and external sources.
• Integrate new data sources as the business grows — APIs, third-party feeds, operational databases, and more.
• Own the reliability, quality, and observability of the data platform end-to-end.

Data Lake & Infrastructure

• Build and evolve our data lake architecture on AWS (S3, Glue, Athena, Lake Formation, or similar).
• Define standards for data storage, partitioning, schema management, and access control.
• Ensure data is well-organized, well-documented, and trustworthy.

Data Services & Exposure

• Build web services and APIs that expose data to internal teams, products, and AI systems.
• Enable data consumers — engineers, analysts, agents — to access the right data in the right shape.

Analytics & ML

• Analyse data to surface patterns, anomalies, and business insights.
• Collaborate on building and deploying ML models that generate new understanding from our data.
• Work closely with product and engineering teams to translate business questions into data solutions.

Automation & AI

• Use AI tools as a daily driver to accelerate pipeline development, data exploration, and model experimentation.
• Identify opportunities to automate data workflows and reduce manual intervention.
• Stay current with AI and data tooling and bring the best of it into the platform.

Qualifications

• 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).

Requirements

• 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.

Benefits

• Exceptional career growth and strong commitment to talent development.
• A dynamic, forward-thinking company rooted in entrepreneurial culture with flat hierarchies.
• Fully remote with regular in-person gatherings in Istanbul.
• Birthday Retreat: complimentary half-day off on your birthday.
• Five weeks of paid vacation plus the option for additional unpaid leave.