Data Engineering Manager

Summary

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 Manager 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 Manager, you will play a pivotal role in overseeing and shaping our data operations, ensuring that our data is organized, accessible, and effectively managed across the organization. You will lead a talented team, work closely with cross-functional teams, and drive the development of strategies to enhance data quality, availability, and security.

Key Responsibilities:

• Lead Data Management Strategy: Define and execute the data management vision, strategy, and best practices, ensuring alignment with Storable's business goals and objectives.
• Oversee Data Pipelines: Design, implement, and maintain scalable data pipelines using industry-standard tools to efficiently process and manage large-scale datasets.
• Ensure Data Quality & Governance: Implement data governance policies and frameworks to ensure data accuracy, consistency, and compliance across the organization.
• ETL Development: Build, optimize, and maintain ETL pipelines for ingesting, transforming, and delivering large datasets from multiple sources.
• Workflow Orchestration: Manage and schedule complex workflows using Apache Airflow.
• Query Engines & Processing Frameworks: Leverage Trino (Presto), Apache Spark, and other
• Manage Cross-Functional Collaboration: Partner with engineering, product, and business teams to make data accessible and actionable, and ensure it drives informed decision-making.
• Optimize Data Infrastructure: Leverage modern data tools and platforms (e.g., AWS, Apache Airflow, Apache Iceberg) to create an efficient, reliable, and scalable data infrastructure.
• Monitor & Improve Performance: Proactively monitor data processes and workflows, troubleshoot issues, and optimize performance to ensure high reliability and data integrity.
• Mentorship & Leadership: Lead and develop a team of data engineers and analysts, fostering a collaborative environment where innovation and continuous improvement are valued.

Qualifications:

• Proven Expertise in Data Management: Significant experience in managing data infrastructure, data governance, and optimizing data pipelines at scale.
• Technical Proficiency: Strong hands-on experience with data tools and platforms such as Apache Airflow, Apache Iceberg, and AWS services (S3, Lambda, Redshift, Glue, Athena).
• Data Pipeline Mastery: Familiarity with designing, implementing, and optimizing data pipelines and workflows in Python or other languages for data processing.
• Hands-on experience with Trino/Presto and Apache Spark for distributed data processing.
• Solid understanding of data modeling, warehousing concepts, and schema design.
• Experience with Data Governance: Solid understanding of data privacy, quality control, and governance best practices.
• Leadership Skills: Ability to lead and mentor teams, influence stakeholders, and drive data initiatives across the organization.
• Analytical Mindset: Strong problem-solving abilities and a data-driven approach to improving business operations.
• Excellent Communication: