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Entry Level Databricks Data Engineer Jobs in Seattle, WA

Databricks

Customer Enablement Specialist

Bellevue, WA · On-site

Databricks certifications or willingness to certify (Data Engineer Associate, Databricks certifications (or willingness to obtain within 6 months). * Background in SaaS, cloud, or data platforms ...

SynergisticIT

Entry Level ML Engineer

Seattle, WA

Currently, we are looking for entry-level software programmers, Java Full stack developers, Python ... data visualization tools Preferred skills: NLP, Text mining, Tableau, PowerBI, Databricks ...

Databricks

Program Manager, Product

Bellevue, WA · On-site

$132K - $181K/yr

GAQ426R82 About the Role As a Program Manager for Product Legal at Databricks, you will sit at the intersection of cutting-edge data/AI innovation, software engineering, and global compliance.

Pwc

AI & GenAI Data Scientist - Manager

Seattle, WA · On-site

$99K - $232K/yr

In this role at PwC, you will apply data, algorithms, and software engineering to build and deploy ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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Entry Level Databricks Data Engineer information

See Seattle, WA salary details

$34.1K

$78.9K

$134.3K

How much do entry level databricks data engineer jobs pay per year?

As of Jun 21, 2026, the average yearly pay for entry level databricks data engineer in Seattle, WA is $78,936.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,600.00 and $89,300.00 per year, depending on experience, location, and employer.

What is an Entry Level Databricks Data Engineer?

An Entry Level Databricks Data Engineer is a professional who uses Databricks, a cloud-based data analytics platform, to design, build, and maintain data pipelines. They are responsible for preparing and processing large datasets, ensuring data quality, and enabling analytics and machine learning workflows. Typically, they work with tools such as Apache Spark, SQL, and Python, and collaborate with data analysts and data scientists to deliver data-driven solutions. As entry-level engineers, they are expected to have foundational knowledge of data engineering concepts and be eager to learn more advanced techniques on the job.

What are the key skills and qualifications needed to thrive as an Entry Level Databricks Data Engineer, and why are they important?

To thrive as an Entry Level Databricks Data Engineer, you need a foundational understanding of data engineering concepts, SQL, and Python or Scala, typically supported by a relevant degree in computer science or a related field. Familiarity with Databricks, Apache Spark, cloud platforms (like AWS or Azure), and optional certifications such as Databricks Data Engineer Associate are highly valuable. Strong analytical thinking, attention to detail, and effective communication skills help you collaborate with teams and solve complex data challenges. These skills and qualities are essential for building reliable data pipelines, ensuring data quality, and delivering actionable insights in a fast-paced environment.

What are some common challenges faced by entry-level Databricks Data Engineers, and how can they effectively overcome them?

Entry-level Databricks Data Engineers often face challenges such as learning to optimize Apache Spark jobs, managing complex data pipelines, and understanding cloud-based workflows. To overcome these, it's important to dedicate time to hands-on practice with Databricks notebooks, collaborate closely with more experienced engineers, and actively participate in code reviews and team discussions. Leveraging Databricks' extensive documentation and community forums can also help troubleshoot issues and stay updated on best practices.
What are the most commonly searched types of Databricks Data Engineer jobs in Seattle, WA? The most popular types of Databricks Data Engineer jobs in Seattle, WA are:
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Entry Level Databricks Data Engineer jobs near you
AI & Data - Data Engineer

AI & Data - Data Engineer

Central Business Solutions

Seattle, WA • On-site

$130K - $156K/yr

Full-time

Posted 22 days ago

Job description

Responsibilities
1. Ingest and process data from Salesforce (Investments), Dynamics 365 & Coupa (Finance), Workday (HR), Concur (Operations), and external program/partner data (e.g., Health, Education).
2. Build and maintain pipelines in Databricks, DBT, and Snowflake to deliver curated datasets for AI/ML.
3. Design simple, reusable data models to support training and inference.
4. Implement data quality tests, documentation, and lineage in DBT
5. Ensure performance optimization, cost efficiency, and compliance with governance standards.
6. Collaborate with Knowledge Management (AI/Data Science) team to provide feature ready datasets.
Requirements
1. Hands-on experience with Databricks (PySpark/SQL, Unity Catalog), DBT (models, tests, docs), and Snowflake (SQL, performance tuning).
2. Strong background in ETL/ELT pipeline development.
3. Experience with enterprise SaaS systems (Salesforce, D365, Coupa, Workday, Concur).
4. Solid SQL and Python skills; knowledge of data quality frameworks.

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