Senior Software Engineer, Data Platform

About the position

Material Bank is a fast-paced, high-growth technology company and created the world's largest material marketplace for the Architecture and Design industry, providing the fastest and most powerful way to start and manage a design project. The position involves designing, building, and operating the enterprise data lakehouse using open data stack components, developing monitoring frameworks, managing data transformation pipelines, and collaborating with business stakeholders to ensure high-quality data products. The role also includes evaluating new technologies and leading the development of a data catalog.

Responsibilities

• Design, build, and operate the enterprise data lakehouse using open data stack components.
• Develop and maintain a robust monitoring and observability framework for tracking data pipeline health, performance, and data quality.
• Build and manage scalable, testable, and version-controlled data transformation pipelines using dbt and Git-based workflows.
• Implement CI/CD pipelines for data workflows to ensure safe and efficient deployments.
• Work closely with business stakeholders to gather requirements, support self-service analytics, and ensure the delivery of reliable, high-quality data products.
• Design and enforce data contracts, lineage tracking, and documentation standards to promote trust and transparency in the data platform.
• Continuously evaluate and adopt new technologies, tools, and open-source frameworks to improve the data engineering ecosystem.
• Lead the development and maintenance of our data catalog.

Requirements

• 5+ years of experience in data engineering or software engineering, with deep expertise in building and scaling batch and streaming pipelines.
• Strong proficiency in Python and SQL, with experience writing efficient queries and reusable data transformations.
• Expert-level knowledge of dbt (Core & Cloud), including macro development, model testing, documentation, and deployment practices.
• Strong understanding of modern data modeling techniques and architecture patterns (e.g., medallion architecture, star/snowflake schema).
• Experience developing custom hooks/operators in Apache Airflow for orchestration.
• Proficiency in working with cloud platforms (preferably AWS) and cloud-native data infrastructure.

Nice-to-haves

• Experience with ClickHouse for OLAP workloads and Airbyte for replication.
• Familiarity with Docker and Kubernetes for containerized and scalable deployments.
• Experience working with OpenMetadata.

Benefits

• Generous PTO, Sick Days, Paid National Holidays.
• Health benefits including medical, dental, vision, and short-term/long-term disability plans.
• 401(k) eligible after your first 90 days employed.
• Time off to give back to the community through sponsored events.
• Flexible work schedules with a hybrid working model.