The Lead Data Engineer will be the primary architect and builder of our data ecosystem enabling data-driven capabilities. You will oversee data integration work, including building and maintaining the data warehouse and data integrations, and ensuring industry-compliant data governance.
Responsibilities
- Lead the evaluation, selection, and implementation of a scalable data tech stack that balances performance with cost-effectiveness.
- Design and implement robust data ingestion flows across on-premise and cloud environments, ensuring high-quality, reliable data models for analytics use cases.
- Collaborate with regional and cross-functional teams to define data requirements and design solutions that align with business objectives.
- Establish and oversee data governance and quality frameworks, ensuring data accuracy, consistency, and compliance with regulatory standards (e.g. PDPO, GDPR).
Requirements
- Bachelor’s degree or above in Computer Science, Data Engineering, Information Systems, or a related discipline
- 6–9 years of experience in the data engineering field, ideally with a focus on building production data pipelines for analytics use cases within real estate, PropTech, or adjacent professional services sectors
- Strong proficiency in SQL and Python, with hands‑on experience with NoSQL databases and ETL/ELT orchestration tools (Airflow, dbt, Alteryx or similar)
- Deep knowledge of cloud big data platforms such as Azure, AWS, Databricks or similar, and hybrid (cloud/on‑prem) data integration
- Familiarity with CI/CD, version control, and DevOps practices
- A self‑starter who thrives in lean environments and has a strong sense of ownership
- Strong project management and communication skills, with the ability to communicate complex ideas effectively