Job Description

Data Engineer

Our client is seeking a Data Engineer to take ownership of end-to-end data processes within a growing, values-driven organization. This individual will play a key role in ensuring data is accurate, reliable, and actionable across the business. The ideal candidate is hands-on, detail-oriented, and comfortable working across the full data lifecycle—from ingestion and transformation to reporting and stakeholder enablement.

This role is a hybrid model in Portland, Oregon or Lakewood, Washington.

Data Engineer Responsibilities

• Own data quality across systems by identifying, troubleshooting, and resolving inconsistencies and inaccuracies.
• Design, build, and maintain scalable ETL/ELT pipelines to transform raw data into clean, structured datasets.
• Manage data ingestion processes from multiple internal and external sources, including APIs and databases.
• Develop and optimize SQL queries, data models, and schemas to support analytics and reporting needs.
• Create and maintain dashboards and reports in Power BI, ensuring they are accurate, user-friendly, and actionable.
• Partner with business stakeholders to translate requirements into data solutions and meaningful insights.
• Monitor pipeline performance and reliability, proactively addressing failures and inefficiencies.
• Contribute to data architecture design, including data lake structure and best practices.
• Document data sources, transformations, and workflows to support transparency and scalability.
• Collaborate cross-functionally with engineering and business teams to support data-driven decision making.

Data Engineer Qualifications

• 3+ years of experience in a data engineering, analytics engineering, or similar role with ownership of data pipelines and reporting.
• Strong proficiency in SQL, including complex queries, joins, and performance optimization.
• Hands-on experience with Python for data transformation, scripting, and automation.
• Proven experience building and maintaining Power BI dashboards, including data modeling and DAX.
• Experience designing and managing ETL/ELT processes and understanding when to apply each approach.
• Familiarity with cloud-based data platforms, preferably within a Microsoft ecosystem (e.g., Azure Data Factory, Synapse, or similar tools).
• Experience working with data lakes and modern data architecture concepts.
• Ability to work with APIs and semi-structured data formats such as JSON.
• Strong communication skills with the ability to explain data concepts to non-technical stakeholders.
• Detail-oriented with a strong sense of ownership and accountability for data accuracy.

Preferred:

• Experience with ERP or CRM systems as data sources (e.g., Microsoft Dynamics environments).
• Familiarity with transformation frameworks such as dbt.
• Experience working in smaller, collaborative teams with broad responsibilities.
• Background supporting financial or operational data where accuracy is critical.

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