Data Engineer

United StatesRemoteFull-timemid

Data EngineerData

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Quick Summary

Overview

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer based in United States. As a Data Engineer,

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Data EngineerData

As a Data Engineer, you will design, build, and enhance modern cloud-based data platforms that power enterprise analytics, reporting, and operational decision-making. You will work extensively with Snowflake and Microsoft Fabric to develop scalable warehouses, lakehouses, data pipelines, and curated data layers. The role combines hands-on engineering with data architecture, integration, performance optimization, and production reliability. You will bring together data from enterprise applications, ERP and financial systems, APIs, databases, and other sources. Working closely with technical teams and business stakeholders, you will translate evolving requirements into dependable data solutions. This is a primarily remote opportunity with occasional on-site meetings in Portland, Oregon, when required.

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 structured or semi-structured sources.
Develop logical, physical, and dimensional data models supporting analytics, business intelligence, enterprise reporting, and downstream applications.
Implement Microsoft Fabric solutions using Data Factory, Lakehouse, OneLake, data engineering workloads, and Power BI integration.
Design and optimize Snowflake environments, including warehouse structures, ELT processes, performance tuning, and scalable data-processing patterns.
Establish orchestration, monitoring, and observability practices to maintain reliable production data workflows.
Build and support REST API integrations and other 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.

Requirements

~1 min read

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 working with cloud-based data platforms in Azure and/or AWS environments.
Experience with relational database technologies such as SQL Server, PostgreSQL, MySQL, Oracle, or DB2, as well as structured and semi-structured datasets.
Familiarity with Databricks, PySpark, Delta Lake, NoSQL, 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.
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.