Data Engineer

Role Summary We 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 AI Disclaimer & Accommodations We may use AI-enabled tools to assist with certain parts of our hiring process, including application review and candidate evaluation. These tools support our team and are used with human oversight. All final hiring decisions are made by humans. If you require reasonable accommodations during the application process or have questions about our hiring process, please contact OWSC@walkeradvertising.com.