Data Engineer

Metasys Technologies/NVISH•Portland, OR

10d•Remote

About The Position

Data Engineer to design, build, and enhance modern cloud-based data platforms that support enterprise analytics, reporting, and operational needs. The ideal candidate brings deep hands-on expertise with Snowflake and Microsoft Fabric, strong data warehouse and pipeline development skills, and the ability to translate complex data requirements into scalable, reliable solutions. This role is mostly remote with occasional on-site meetings in Portland, Oregon when required.

Requirements

5+ years of experience in data engineering, software engineering, or a related technical discipline.
Advanced hands-on experience with Snowflake and Microsoft Fabric, including Fabric Data Factory, Lakehouse/OneLake, data engineering workloads, and Power BI integration.
Strong Python development and advanced SQL skills, with demonstrated experience building scalable ETL/ELT pipelines and enterprise data warehouse solutions.
Experience integrating data from ERP, financial, or operational platforms; experience extracting and integrating NetSuite data into a data warehouse is highly preferred.
Strong understanding of modern data warehouse, lakehouse, dimensional modeling, and medallion architecture concepts.
Experience with cloud-based data platforms in Azure and/or AWS environments.
Experience working across relational database technologies such as SQL Server, PostgreSQL, MySQL, Oracle, or DB2, as well as structured and semi-structured datasets.
Strong communication and problem-solving skills with the ability to collaborate across technical and business teams, manage evolving requirements, and take ownership of reliable production data solutions.

Nice To Haves

Familiarity with Databricks, PySpark, Delta Lake, NoSQL or distributed data technologies, and workflow orchestration tools such as Airflow, Prefect, or Dagster is preferred.
Experience with REST APIs, streaming or event-driven technologies, CI/CD practices, or modern application frameworks is a plus.

Responsibilities

Design and develop scalable cloud data platforms, including data warehouses, data lakes, and lakehouse environments using Snowflake and Microsoft Fabric.
Build and maintain production-grade ETL/ELT pipelines, ingestion processes, transformation frameworks, and curated data layers using Python, PySpark, and SQL.
Integrate data from enterprise applications, ERP and financial systems, APIs, relational databases, flat files, and other structured or semi-structured sources.
Develop logical, physical, and dimensional data models that support analytics, business intelligence, enterprise reporting, and downstream applications.
Implement Microsoft Fabric solutions utilizing Data Factory, Lakehouse, OneLake, data engineering workloads, and integration with Power BI.
Design and optimize Snowflake environments, including data warehouse structures, ELT processes, performance tuning, and scalable data processing patterns.
Establish orchestration, monitoring, and observability practices to maintain reliable and efficient production data workflows.
Build and support REST API integrations and other data services for inbound and outbound data exchange.
Optimize data platforms and pipelines for performance, scalability, reliability, and cost efficiency.
Partner with technical teams and business stakeholders to define data requirements, guide architecture decisions, and establish data engineering best practices.