Data Engineer I

Storable is on a mission to power the future of storage by helping businesses manage and grow their self-storage operations. They are seeking a Data Engineer to support the design, development, and maintenance of data pipelines and infrastructure, ensuring data is reliable and accessible for reporting and analytics.

Responsibilities:

• 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
• 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
• Support workflow scheduling and monitoring using Apache Airflow
• Troubleshoot task failures and assist in improving workflow reliability
• Work with distributed processing frameworks such as Apache Spark
• Support querying and data access using tools like Trino (Presto) and AWS services
• Help implement data validation checks and monitoring
• Support data documentation and adherence to governance best practices
• Assist in maintaining consistency across datasets
• 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
• 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

Requirements:

• 1–3 years of experience in data engineering, analytics engineering, or related field
• Experience building or supporting data pipelines in cloud environments
• 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
• Understanding of ETL/ELT processes
• Familiarity with data quality principles
• Exposure to schema design and analytical datasets
• 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
• Exposure to distributed data processing tools (Spark preferred)
• Exposure to Apache Iceberg or modern table formats
• Experience working with BI tools such as Looker or Tableau
• Experience in a SaaS or product-led environment