About Us

Real Estate Analytics is a company at the forefront of AI and real estate technology. We are looking for an experienced Senior Data Engineer to join our data team. If you are passionate about building scalable data solutions and transforming raw data into actionable insights that drive business decisions, we want to hear from you. This is an exciting opportunity to shape the future of our data strategy and make a significant impact in a dynamic environment.

What You'll Do

As a Senior Data Engineer, you will be a key player in designing, building, and maintaining the infrastructure that powers our data-driven culture. Your responsibilities will include:

• Architect and Build Scalable Infrastructure: Design, develop, and maintain robust and scalable data pipelines and architectures to support our company's long-term growth.
• Develop Resilient Data Extraction Programs: Build and manage sophisticated ETL/ELT processes for a variety of data sources, including RESTful APIs and GraphQL, ensuring reliability with built-in failure recovery.
• Lead Data Warehousing Initiatives: Take charge of setting up and maintaining our data warehouse for new products, ensuring it aligns with our expanding business needs.
• Champion Code Excellence and Collaboration: Establish and oversee Git workflows for version control and code deployment. You will also review and optimize code from team members, mentoring them on best practices for efficiency and quality.
• Ensure Database Integrity and Performance: Conduct audits and reviews of database changes to maintain strong controls. Your expertise in data modeling, indexing, and query optimization will be crucial.
• Collaborate with Key Stakeholders: Work closely with data scientists, analysts, and business leaders to understand their requirements and provide effective technical solutions that meet their needs.

What You'll Bring

We are looking for a candidate with a strong foundation in computer science and extensive experience in data engineering.

Required Qualifications:

• A degree in Computer Science, Computer Engineering, Data Analytics, or a related technical field.
• 5-7 years of professional experience in a data-focused role.
• Expert-level proficiency in Python and SQL, with a deep understanding of database design and experience managing large volumes of data.
• Solid knowledge of data modeling, indexing strategies, and query optimization techniques.
• Proven experience with data lakes, including the integration of diverse data sources.
• Strong familiarity with version control systems like Git and collaborative development workflows.
• Excellent communication and teamwork skills, with a proven ability to collaborate effectively across different teams.

Preferred Qualifications (Bonus Points):

• Hands-on experience with Apache Airflow, dbt, ClickHouse, or MongoDB
• Experience with cloud platforms such as Google Cloud Platform (GCP) or Amazon Web Services (AWS).
• Knowledge of distributed computing, parallel processing, and working with large-scale datasets.