Data Engineer – Databricks

BuzzClan; Beaverton (OR); Hybrid; USD 110,000 - 160,000; Full time

Job summary

BuzzClan seeks an experienced Data Engineer in Beaverton to design, build and maintain scalable data pipelines using Databricks, PySpark, Spark SQL and Delta Lake. You will work with Python, SQL and cloud platforms to deliver enterprise data solutions.

This contract-to-hire role requires 3 days onsite per week in Beaverton, OR, and collaboration with data architects, developers and stakeholders to implement robust data workflows and governance.

Qualifications

• Hands-on experience designing and building scalable ETL/ELT pipelines.
• Strong Databricks, PySpark, Spark SQL, Delta Lake and Python/SQL skills.
• Experience with cloud platforms and modern data engineering practices.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines and enterprise data solutions.
• Develop and optimize data processing using Databricks, PySpark, Spark SQL, and Delta Lake.
• Build reliable data pipelines using Python and SQL.
• Implement data integration across enterprise sources.
• Work with Azure/AWS/GCP, preferably Azure, and use CI/CD/DevOps practices.

Skills

Databricks

PySpark

Spark SQL

Delta Lake

Python

SQL

Data modeling

Data warehousing

CI/CD

DevOps

Tools

Azure

AWS

GCP

Azure Data Factory

Apache Airflow

Delta Live Tables

Unity Catalog

Structured Streaming

Git

Job description

Data Engineer – Databricks Location: Beaverton, OR - Hybrid (3 Days Onsite) Contract-to-Hire

Job Overview

We are seeking an experienced Data Engineer with strong Databricks expertise to design, develop, and maintain scalable enterprise data pipelines and data engineering solutions. The ideal candidate will have hands‑on experience with Databricks, PySpark, Spark SQL, Delta Lake, Python, and SQL, along with experience in cloud platforms and modern data engineering practices. Candidates must be local to or able to work onsite in Beaverton, Oregon 3 days per week.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines and enterprise data solutions.
• Develop and optimize data processing solutions using Databricks, PySpark, Spark SQL, and Delta Lake.
• Build reliable and high-performance data pipelines using Python and SQL.
• Implement data integration and transformation processes across various enterprise data sources.
• Work with cloud platforms such as Azure, AWS, or GCP, with preference for Azure.
• Develop and manage data workflows using orchestration tools such as Azure Data Factory (ADF) and/or Apache Airflow.
• Apply data modeling, data warehousing, and performance optimization best practices.
• Implement data quality, scalability, reliability, and performance improvements across data platforms.
• Use Git, CI/CD, and DevOps practices to support automated and reliable data deployments.
• Collaborate with business stakeholders, data architects, developers, and other cross‑functional teams to deliver enterprise data solutions.
• Troubleshoot complex data pipeline and processing issues and provide effective technical solutions.
• Contribute to modern Databricks capabilities such as Delta Live Tables (DLT), Unity Catalog, and Structured Streaming where applicable.