Data Engineer II

Storable is on a mission to power the future of storage, helping businesses manage their self-storage operations. As a Data Engineer II, you will design, develop, and optimize the data platform, ensuring data is reliable, accessible, and actionable while collaborating with various teams.

Responsibilities:

• Build & Maintain Data Pipelines Develop and maintain scalable data pipelines to ingest, process, and transform data from multiple sources
• ETL Development Support the design and optimization of ETL/ELT workflows to ensure efficient and reliable data delivery
• Workflow Orchestration Work with tools like Apache Airflow to schedule and manage data workflows
• Data Quality & Reliability Help implement data quality checks, validation processes, and monitoring to ensure accuracy and consistency
• Data Modeling & Warehousing Contribute to data modeling efforts, schema design, and data warehouse optimization
• Query & Processing Frameworks Utilize tools such as Trino (Presto), Apache Spark, or similar technologies to support distributed data processing
• Infrastructure & Performance Optimization Assist in improving performance, scalability, and cost-efficiency of data systems using modern cloud platforms (AWS)
• Cross-Functional Collaboration Partner with stakeholders across engineering, product, and business teams to understand data needs and deliver solutions
• Monitoring & Troubleshooting Identify issues in pipelines and workflows, troubleshoot effectively, and implement long-term fixes

Requirements:

• 5+ years of experience in data engineering, data infrastructure, or related roles
• Experience with Python or similar languages for data processing
• Familiarity with SQL and distributed query engines (e.g., Trino/Presto)
• Exposure to Apache Spark or similar processing frameworks
• Experience with workflow orchestration tools (e.g., Apache Airflow)
• Experience with AWS services such as S3, Redshift, Glue, or Athena
• Understanding of data modeling, warehousing concepts, and schema design
• Familiarity with data validation, quality checks, and governance best practices
• Strong analytical mindset with the ability to troubleshoot and optimize data systems
• Ability to communicate clearly with both technical and non-technical stakeholders
• Experience with modern data formats (e.g., Apache Iceberg)
• Exposure to BI/visualization tools (e.g., Looker, Tableau)
• Experience working in a SaaS or product-driven environment