Data Engineer I

Data Engineer

At Storable, we're on a mission to power the future of storage. Our innovative platform helps businesses manage, track, and grow their self-storage operations, and we’re looking for a Data Engineer to join our data-driven team. Storable is committed to leveraging cutting-edge technologies to improve the efficiency, accessibility, and insights derived from data, empowering our team to make smarter decisions and foster impactful growth.

As a Data Engineer, you will support the design, development, and maintenance of data pipelines and infrastructure. You will partner closely with senior data engineers, analytics teams, and cross-functional stakeholders to help ensure data is reliable, well-structured, and accessible for reporting and analytics use cases.

Key Responsibilities

Support Data Pipelines

• Assist in building, maintaining, and optimizing scalable data pipelines
• Support ingestion, transformation, and validation of structured and semi-structured data
• Help monitor and troubleshoot pipeline performance issues
  
  ETL / ELT Development

• Contribute to developing and maintaining ETL/ELT workflows
• Write clean, maintainable transformation logic in SQL and/or Python
• Ensure data is delivered accurately and on time to downstream systems
  
  Workflow Orchestration

• Support workflow scheduling and monitoring using Apache Airflow
• Troubleshoot task failures and assist in improving workflow reliability
  
  Query Engines & Processing Frameworks

• Work with distributed processing frameworks such as Apache Spark
• Support querying and data access using tools like Trino (Presto) and AWS services
  
  Data Quality & Governance

• Help implement data validation checks and monitoring
• Support data documentation and adherence to governance best practices
• Assist in maintaining consistency across datasets
  
  Cross-Functional Collaboration

• Partner with analytics, product, and engineering teams to understand data needs
• Translate business requirements into technical data solutions with guidance
• Contribute to improving data accessibility and usability
  
  Infrastructure & Optimization

• Work within AWS-based data environments (S3, Glue, Athena, Redshift, etc.)
• Support performance tuning and cost optimization efforts
• Follow best practices in data modeling and schema design
  
  Qualifications
  
  Experience

• 1–3 years of experience in data engineering, analytics engineering, or related field
• Experience building or supporting data pipelines in cloud environments
• Exposure to distributed data processing tools (Spark preferred)
  
  Technical Skills

• Proficiency in SQL
• Experience with Python or similar language for data processing
• Familiarity with Apache Airflow (or other orchestration tools)
• Exposure to AWS services such as S3, Redshift, Glue, Athena, or Lambda
• Basic understanding of data modeling and warehousing concepts
  
  Data Fundamentals

• Understanding of ETL/ELT processes
• Familiarity with data quality principles
• Exposure to schema design and analytical datasets
  
  Soft Skills

• Strong problem-solving mindset
• Clear written and verbal communication skills
• Eagerness to learn and grow within a collaborative environment
• Ability to take feedback and iterate quickly
  
  Bonus Points

• Exposure to Apache Iceberg or modern table formats
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