Role SummaryWe are seeking a Data Engineer to maintain and engineer data across both our codeless (Domo) and code-based (dbt) environments. You will build and support reliable data pipelines, transform raw data into trusted, analytics-ready datasets, and partner with analysts and business stakeholders to keep reporting accurate and timely. dbt experience is a plus.
Key Responsibilities- Build, maintain, and monitor data pipelines and ETL/ELT workflows in Domo, including Magic ETL dataflows, connectors, and DataSets.
- Develop and maintain data transformations and models in dbt, following version control, testing, and documentation best practices.
- Ingest data from internal systems, third-party platforms, advertising and marketing APIs, and flat files into the data warehouse.
- Design and maintain data models and analytics-ready datasets that support reporting, dashboards, and self-service analytics.
- Implement data quality checks, validation, and alerting; troubleshoot and resolve pipeline failures and data discrepancies.
- Optimize query performance, refresh schedules, and warehouse costs across Domo and dbt environments.
- Partner with analysts, marketing, and business stakeholders to gather requirements and translate them into technical solutions.
- Maintain documentation for data sources, lineage, definitions, and processes.
- Apply data governance, security, and access control standards to protect sensitive data.
- Contribute to the migration of codeless workflows to code-based solutions where it improves scalability and maintainability.
Required Qualifications- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.
- 1-2 years of experience in data engineering, analytics engineering, or a similar role.
- Advanced SQL skills, including complex joins, window functions, CTEs, and performance tuning.
- Working knowledge of data warehousing concepts, dimensional modeling, and ETL/ELT patterns.
- Strong troubleshooting skills and attention to detail, with commitment to data accuracy.
- Clear written and verbal communication skills, and the ability to work with technical and non-technical partners.
Preferred Qualifications- Experience developing, testing, and deploying dbt models (dbt Core or dbt Cloud).
- Experience with a cloud data warehouse such as Snowflake, BigQuery, Redshift, or Azure Synapse.
- Proficiency in Python for scripting, automation, and API integrations.
- Experience with Git and CI/CD workflows for data projects.
- Familiarity with orchestration tools such as Airflow, Dagster, or Prefect.
- Experience with marketing, advertising, or CRM data sources (for example Google Ads, Meta, Google Analytics, or Salesforce).
- Experience with BI tools such as Domo, Tableau, Power BI, or Looker.
- Knowledge of data governance, data cataloging, and data observability practices.
Technical Skills and Tools- Languages: SQL (required), Python (preferred).
- Platforms: BI analysis tools, dbt (preferred), cloud data warehouse.
- Practices: Version control (Git), data testing, documentation, and code review.
- Integrations: REST APIs, flat files, and third-party marketing and advertising connectors.
Benefits/Perks- 3 Weeks Paid Time Off
- 12 Weeks of Paid Parental Leave
- Comprehensive Insurance Coverage (Medical, Dental, Vision, etc.)
- 401(k) Retirement Savings Plan
- Wellness Initiatives/Employee Assistance Program
- Rewards and Recognition Programs
- Career Development Opportunities
Pay Range$85,000 - $90,000 base salary + 10% annual bonus
