Senior Data Engineer
Who We Are
Are you a Senior Data Engineer looking for an opportunity to help scale the data backbone behind an AI-driven real estate platform trusted by companies worldwide?
At Restb.ai, we specialize in industry-specific visual recognition, helping businesses unlock powerful insights through AI-driven automation. We don’t just recognize objects (that’s so 2016), we teach computers to understand intangible visual concepts like “this room has natural light.”
By joining our team, you will play a critical role in owning and evolving our Data Engineering tech stack as we grow from startup to scale-up, working hand-in-hand with our Data Lead and Product team to turn ambitious ideas into clean, reliable technical solutions. If you thrive on solving complex data modeling and pipeline challenges, driving engineering excellence at scale, and have a passion for building things that last, we’d love to meet you!
Your Role
We are looking for a Senior Data Engineer who is passionate about building resilient, scalable data infrastructure and always looking for smarter ways to tackle complex data challenges. As our Senior Data Engineer, you will support our Data Lead in managing the team, take ownership of our Data Engineering tech stack end-to-end, and work closely with fellow data engineers to help shape our technical direction and standards.
You’ll be a key player in ensuring our data platform scales reliably as the company grows, and that Product and Data teams can move fast with confidence in the data they depend on. This role is envisioned as a key technical leadership track within our data organization as we mature our real estate data platform.
The usual day-to-day tasks include designing and reviewing dbt models and Airflow DAGs, syncing with Product to translate business requirements into clear technical solutions, mentoring fellow data engineers, and troubleshooting and optimizing pipelines across our AWS-based data lake.
The role will be completely in English, and CVs/resumes in other languages will not be considered.
What You’ll Do
- Own the data engineering tech stack: Take end-to-end ownership of our dbt, Airflow, and AWS-based data lake stack, keeping it scalable, well-tested, and reliable as data volumes and use cases grow.
- Translate product needs into technical solutions: Sync regularly with Product to understand business goals and turn them into clear, well-scoped technical designs the team can execute against.
- Architect and build pipelines: Design robust, idempotent ETL pipelines in Python and Airflow, including custom operators and extractors, feeding a well-structured S3 data lake.
- Shape our data modeling strategy: Guide dimensional and warehouse modeling decisions across the team, reasoning about Hub/Link/Satellite structures and Kimball star schemas, to keep our models scalable and easy to reason about.
- Support team growth: Partner with the Data lead to mentor other data engineers, review technical designs and pull requests, and help raise the bar on engineering practices across the team.
- Drive DataOps maturity: Champion monitoring, alerting, testing, and CI/CD practices that keep our pipelines observable and trustworthy as we scale.
What We’re Looking For
- Trajectory: helping a startup scale into a scale-up, you’ve seen firsthand how data platforms need to evolve as volume, team size, and complexity grows.
- SQL & dbt: Strong SQL skills paired with solid dbt experience.
- Python & orchestration: Strong Python skills (Pandas/Polars), particularly for building Airflow DAGs, custom operators, and extractors.
- Apache Airflow: Experience designing production DAGs.
- Data lakehouse: Solid understanding of data lakehouse and medallion architecture.
- Data modeling depth: Comfort reasoning about both Data Vault concepts (Hubs/Links/Satellites) and Kimball-style star schemas.
- DataOps mindset: A strong operational mindset around monitoring, testing, and reliability, with AWS experience a strong plus.
- ETL design: Demonstrated ability to design and maintain robust ETL pipelines end-to-end.
- ElasticSearch/Opensearch: Knowledge and understanding of No-SQL DBs such as this ones.
- AWS Kinesis: Familiarity its a plus.
- Lake/warehouse engines: Experience with modern engines such as DuckDB and Apache Iceberg.
- Migration/backfill experience: safely reprocessing large historical datasets, idempotent pipelines, replay-from-raw patterns.
Employment Type
- Type: Permanent / Full-time
- Start Date: Ready to start ASAP
What makes working at restb.ai great
- Make an Impact: Your work will directly shape AI-driven real estate technology.
- Innovation-Driven Culture: Work with cutting-edge AI and industry-leading solutions.
- Global Exposure: Be part of an international company that works with some of the largest companies in the world.
- Dynamic Team: Thrive in an open environment with young, driven, and dynamic team members.
- In-Office Perks: Free in-office snacks, beverages, hot drinks, salads, and a free team lunch every Wednesday.
- Wellness & Culture: Free in-office physical therapy sessions and quarterly team-building events.
- Growth: Career development training and clear paths for internal growth.
- Flexibility: Hybrid office/remote working policy and comprehensive health insurance.
- Location: Barcelona-based, working worldwide! Do we need to say more?
Talent with vision grows here
join us in achieving the impossible.