Data Engineer

Walker Advertising is hiring a Data Engineer to maintain and engineer data across Domo and dbt environments. The role builds reliable data pipelines, transforms raw data into analytics-ready datasets, and partners with analysts and business stakeholders to support accurate, timely reporting.

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

Requirements:

• 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
• SQL (required)
• 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
• Python (preferred)
• dbt (preferred)