Staff Software Engineer - Data

About us: At Storable , our Data Engineering team plays a pivotal role in shaping the future of self-storage technology. We are a group of passionate engineers dedicated to designing and building robust, scalable, and secure data platforms that power data-driven insights for our customers. Our mission is to transform complex data into actionable intelligence, enabling self-storage businesses to operate more efficiently and grow faster. Leveraging cutting-edge technologies like Apache Airflow , Apache Iceberg , and advanced AWS services , we ensure our systems are optimized for performance, reliability, and scalability. Collaboration is at the heart of everything we do. Our team works closely with cross-functional teams, including product, analytics, and business operations, to align our solutions with Storables broader vision. With a strong emphasis on continuous learning and innovation, we encourage team members to push boundaries and deliver impactful solutions that make a difference. Joining our team means being part of a dynamic environment where your expertise is valued, your ideas are heard, and your work directly contributes to the success of our customers. If you're excited about solving challenging problems and driving innovation in data engineering, Storable is the place for you! Job Description: We are looking for an experienced Staff Software Engineer - Data to lead and innovate within our data engineering efforts. This role is ideal for candidates with 10-15 years of experience in designing, building, and optimizing large-scale data platforms. The successful candidate will work with a team of talented engineers, leveraging cutting-edge technologies to deliver high-quality, scalable data solutions. Key Responsibilities

• Architect, implement, and maintain scalable data platforms and pipelines to support business analytics and data-driven decision-making.
• Build and optimize robust workflows and processes using tools such as Apache Airflow and Apache Iceberg .
• Design scalable and secure data processing and storage solutions on AWS (e.g., S3 , Lambda , Redshift , Glue ).
• Develop, deploy, and maintain high-performance data systems using Python and other relevant technologies.
• Collaborate with cross-functional teams to ensure the alignment of data systems with business needs.
• Drive improvements to data quality, performance, and reliability through proactive monitoring and optimization.
• Mentor and guide junior engineers, fostering technical growth within the team.

• 10-15 years of experience in data engineering , with a strong focus on distributed systems and large-scale data processing.
• Expertise in tools and frameworks such as Apache Airflow , Apache Iceberg , and AWS data services .
• Proficiency in Python , with experience writing clean, efficient, and maintainable code for data processing and ETL tasks.
• Strong knowledge of data modeling, pipeline architecture, and best practices for ETL processes.
• Familiarity with reporting and visualization tools such as Looker (bonus).
• Proven leadership and mentoring skills, with experience in guiding and collaborating with teams.
• Excellent problem-solving skills and a proactive approach to improving systems and processes.

• Strong communication and interpersonal skills to work effectively in a collaborative, fast-paced environment.
• Passion for leveraging modern data tools and frameworks to drive innovation.
• Commitment to staying updated with the latest trends and advancements in data engineering.