Data Engineer

Summary

Join Goldbelly as a Data Engineer and enhance how millions of customers connect with food experiences on our platform. Partner with business leaders and utilize cutting-edge resources to transform our data infrastructure and pipelines. You will collaborate with various engineering and product teams, design and optimize data pipelines, build and maintain robust data systems, and ensure data quality and security. Leverage your expertise in SQL, Python, data modeling, and cloud-based infrastructure to support analytics, reporting, and machine learning applications. This role offers a competitive salary, equity, and benefits.

Requirements

• 3+ years of experience in data engineering and working on large-scale data systems
• Expert level in SQL required
• Skilled in dimensional and normalized data modeling and transformation using tools like dbt Cloud
• Strong understanding of cloud-based data infrastructure
• Experience with BI platforms like Metabase and Sigma Computing for data visualization/dashboard tools
• Experience with data ingestion and ETL pipelines like Fivetran
• Familiarity with event-driven architectures and real-time data streaming using tools like Confluent Kafka
• Proficient in version control with Git and collaborative development on GitHub or GitLab

Responsibilities

• Collaborate closely with full stack engineers, machine learning engineers, data analysts, and product managers to design and optimize data pipelines and ETL processes that drive business decisions
• Design, develop, and maintain robust, scalable data systems to ensure seamless data integration and high availability
• Improve our data infrastructure by optimizing ingestion, storage, and retrieval processes to support analytics, reporting, and machine learning applications
• Help define and ensure data quality, governance, and security best practices are followed across all data workflows
• Build and maintain data models that support business insights and operational reporting
• Apply software engineering best practices, including CI/CD, testing, and version control, to data engineering workflows to ensure reliability and maintainability

Preferred Qualifications

• Proficiency in Python preferred
• Strong understanding of cloud-based data infrastructure (AWS and Snowflake preferred)

Benefits

• Salary range: $140,000 - $190,000 base salary range (dependent on experience level and interview performance)
• Equity (incentive stock options, vested over 4 years)
• Benefits