AI-Driven Data Engineer — Azure & Snowflake Platform

Weyerhaeuser; Seattle (WA); On-site; USD 99,000 - 148,000; Full time

Benefits offered by this job

Medical benefits

401(k) with company match

Paid time off

Career development

Job summary

Weyerhaeuser in Seattle, WA is seeking a Data Engineer to build and operate a scalable data platform supporting reporting, analytics, and AI. You will design ingestion pipelines from SAP, databases, flat files, REST APIs, and SaaS, while ensuring data quality and governance.

The role emphasizes building reliable, metadata‑driven pipelines, leveraging AI to accelerate development, and collaborating with analytics engineers, data scientists, and analysts in a fast‑paced environment.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering or equivalent experience.
• 4+ years of hands‑on data engineering experience building and operating production data pipelines.
• Strong proficiency in Python and SQL.
• Production experience with a cloud‑based ingestion and orchestration platform — Azure Data Factory and Azure Functions preferred, though comparable tools are acceptable.
• Production experience with dbt or a comparable transformation framework, including materialization patterns and test coverage.
• Production experience with Snowflake or similar data platform: loading patterns, access control, performance tuning.
• Experience ingesting from SAP, relational databases, flat files, REST APIs, and SaaS applications.
• Experience implementing incremental/delta load patterns and managing watermarking, CDC, and backfills.
• Working knowledge of Terraform for provisioning cloud resources.
• Solid understanding of data quality, monitoring, and operational support practices.
• Working proficiency with Git, PR workflows, and CI/CD pipelines for data.

Responsibilities

• Design and maintain ingestion pipelines moving data from SAP, relational databases, flat files, REST APIs, message queues, and SaaS into the data lake/Snowflake.
• Extend metadata‑driven and template‑driven ADF frameworks; onboarding is configuration, not hand‑made pipelines.
• Develop Python‑based Azure Functions for custom ingestion logic and API integrations.
• Implement reliable full and incremental load patterns including watermarking and CDC.
• Design and support geospatial data pipelines for analytics and reporting.
• Land raw data in lake, build dbt models into clean silver datasets.
• Collaborate on dimensional modeling and semantic views for AI‑ready datasets.
• Orchestrate end‑to‑end workflows in Azure Data Factory; manage retries and error handling.
• Build monitoring, alerts, and incident response; support off‑hours as needed.
• Tune Snowflake workloads for performance and cost.
• Apply data quality rules and compliance practices; contribute to lineage and catalog efforts.
• Partner with Data Platform Engineers on Terraform for cloud resources; promote best practices.
• Mentor junior engineers and contribute to design reviews and tooling choices.
• Utilize AI tools to accelerate development and testing; document pipelines and standards.
• Communicate technical concepts clearly to technical and non‑technical audiences.

Skills

Python

SQL

Azure Data Factory

Azure Functions

dbt

Snowflake

ETL pipelines

REST APIs

Airflow / Dagster

Terraform

Education

Bachelor's degree in Computer Science or related

Tools

Git

CI/CD pipelines

Job description

Weyerhaeuser in Seattle, WA is seeking a Data Engineer to build and operate a scalable data platform supporting reporting, analytics, and AI. You will design ingestion pipelines from SAP, databases, flat files, REST APIs, and SaaS, while ensuring data quality and governance.

The role emphasizes building reliable, metadata‑driven pipelines, leveraging AI to accelerate development, and collaborating with analytics engineers, data scientists, and analysts in a fast‑paced environment.