Role OverviewWe're seeking a talented and experienced Senior Data Platform Engineer for a full-time, remote position. As a key member of a small, high-autonomy team, you will own the data platform end to end — both designing the pipelines that process real estate data and operating the infrastructure they run on. You'll architect and refine our ETL and aggregation systems while making sure they run reliably, efficiently, and at scale across more than 25 markets.A core part of the team's current focus is ramping up data saturation and quality across markets — building robust deduplication and geo-enrichment pipelines that turn raw, messy listing data into clean, trustworthy data for our clients, and strengthening the orchestration, monitoring, and automation that keep all of it running without hand-holding. You'll step into that effort and help drive it forward.What You'll BringEducational Background: A Bachelor's or Master's degree in Computer Science, Data Science, or a related field (or equivalent practical experience e.g. through a degree in mech. Engeneering or natural sciences (e.g. Physics, Mathematics)).Professional Skills: Exceptional communication and teamwork abilities, with proficiency in English.Experience: At least 5 years in Data Engineering, DataOps, or Platform Engineering, with a track record of building and operating production data systems at scale.Pipeline & ETL Design: Proven experience designing, building, and maintaining scalable ETL/ELT pipelines — batch and streaming — with a focus on correctness, idempotency, and maintainability.Deduplication & Entity Resolution: Hands-on experience with deduplication and entity-matching at scale — fuzzy matching, blocking/candidate generation, geospatial joins, and normalising messy data from many heterogeneous sources.Real Estate Data: Comfort working with large, messy, real-world datasets — ideally property listings or similar — including geo-enrichment and reasoning about data quality and edge cases across markets.Ownership & Independence: Capability to work autonomously in a remote setting and own systems end to end — from pipeline design to production reliability.Operational Mindset: Experience running data systems in production — orchestration, monitoring, alerting, incident response, and data-quality checks. You treat reliability and observability as first-class.Analytical Abilities: Strong problem-solving skills and a solid grasp of Software Engineering principles (SOLID, TDD, Agile, Clean Code, etc.).Technical ExpertisePrimary Language: Expertise in Python programming.Data Modeling & ETL: Strong skills in data modeling and designing efficient transformations — partitioning, schema design, and query optimisation across relational, document, and columnar stores.Databases: Strong experience operating MongoDB, ClickHouse, and Postgres in production (modelling, querying, tuning, backups, recovery).Data Orchestration: Experience with Apache Airflow, including running and monitoring it in production.Containerization & Automation: Solid command of Docker, CI/CD pipelines, and infrastructure-as-code / configuration management (e.g., Ansible, Terraform).Monitoring & Observability: Experience with monitoring and alerting stacks (e.g., Prometheus, Grafana) and building data-quality and reliability checks into pipelines.Storage & Systems: Familiarity with object storage (S3/MinIO) and strong Linux systems fundamentals.Big Data Processing: Experience handling high-volume workloads (billions of rows) is desirable.BenefitsWork Mode: Fully remote position, offering the flexibility to work from anywhere.Compensation: Competitive salary with payments in EUR.Vacation: 25 days of vacation per year to help you recharge and relax.Additional InformationStart Date: ASAP.Probation Period: An initial 6 months to ensure a perfect fit.Contract Duration: A 12-month contract with annual extensions.Work Schedule: Either Monday to Friday or Sunday to Thursday.Join ProperBird to be at the forefront of revolutionising the prop-tech industry through innovative data solutions. 🚀