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Entry Level Databricks Data Engineer Jobs in Seattle, WA

MAQ Software

Software Data Operations Engineer

Redmond, WA · On-site

$85K - $120K/yr

Software Data Operations Engineer Redmond, Washington About MAQ Software MAQ Software enables ... Our team leveraged Azure Databricks for advanced data transformation, Azure Front Door for global ...

SEI

Data and Analytics Consultant

Seattle, WA

Must have experience in architecting and implementing data architecture, data engineering ... Databricks or similar technologies. Advanced Analytics and Data Visualizations * Extensive ...

Accord Technologies Inc.

The Ops / KT Engineer

Seattle, WA · On-site

$128K/yr

... data engineering, DevOps, monitoring, or cloud platform support * Experience preparing KT plans, training content, and transition documents * Familiarity with CloudWatch, Grafana, Airflow, Databricks ...

SynergisticIT

Junior Software Engineer

Kent, WA · On-site

... for entry-level software programmers, Java Full stack developers, Python/Java developers, Data ... NLP, Text mining, Tableau, PowerBI, Databricks, Tensorflow REQUIRED SKILLS For Java /Full stack ...

Futran Tech Solutions Pvt. Ltd.

AIML Engineer

Bellevue, WA · On-site

$92K - $123K/yr

Proficiency in Python, ML Ops, typical data processing tools, pipelines. * Experience building ... Experience with Snowflake, Databricks, Spark and Spark ML. * Experience in evaluating the AI ML ...

Merican

Lead I - Software Engineering

Bellevue, WA

Lead I - Software Engineering Our team builds and maintains data products within the Care & Retail ... Familiarity with Microsoft Fabric, Databricks, and the Azure data stack, including Azure Data Lake ...

Merican

Lead II - Software Engineering

Bellevue, WA

... Data Factory, Databricks-PySpark, and Azure SQL Database and Databricks unity catalogue. The role ... Programming Languages: * Proficiency in Python and PySpark for data transformation, pipeline ...

Satwic Inc

AI/ML Engineer

Bellevue, WA

MsoNormal">Proficiency in Python, ML Ops, typical data processing tools, pipelines. * MsoNormal ... MsoNormal">Experience with Snowflake, Databricks, Spark and Spark ML. * MsoNormal">Experience in ...

Nastech Global

AWS Cloud Engineer

Seattle, WA · On-site

$63.50 - $84.75/hr

AWS Cloud Engineer Location: Seattle, WA/St. Louis, MO/Plano, TX/Dallas, TX/Houston, TX (onsite ... Data Pipeline Development: Design, develop, and optimize ETL/ELT pipelines using AWS & Databricks ...

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All JobsEntry Level Databricks Data Engineer JobsEntry Level Databricks Data Engineer Jobs in Seattle, WA

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:
What are popular job titles related to Entry Level Databricks Data Engineer jobs in Seattle, WA? For Entry Level Databricks Data Engineer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Entry Level Databricks Data Engineer jobs in Seattle, WA look for? The top searched job categories for Entry Level Databricks Data Engineer jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Entry Level Databricks Data Engineer jobs? Cities near Seattle, WA with the most Entry Level Databricks Data Engineer job openings:
Entry Level Databricks Data Engineer jobs near you
Software Data Operations Engineer

Software Data Operations Engineer

MAQ Software

Redmond, WA • On-site

$85K - $120K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 19 days ago

Job description

Job Description
Software Data Operations EngineerRedmond, Washington
About MAQ Software
MAQ Software enables leading companies to accelerate their business intelligence and analytics initiatives. Our AI-powered solutions enable clients to improve their productivity, reduce costs, increase sales, and build stronger customer relationships.
Our clients consistently recognize us for providing architecture and governance frameworks using the Well-Architected Framework, implementing best practices to optimize reports, and building team capability through training programs.
Clients choose to work with us because they are confident in our software delivery. Our confidence results from a commitment to consistent outcomes, reduced time to market, and a transparent workflow. Clients benefit from daily software updates, agile practices, domain expertise, AI adoption, and rapid feedback implementation.
As a premier supplier to Microsoft for over two decades, MAQ Software clients gain extensive insights and engineering practices across the Microsoft platform and can improve their implementations with our breadth and depth of expertise.
As one of the top 25 global partners, Microsoft has awarded MAQ Software eight specializations for meeting their highest standards of service delivery to Fortune 500 companies.
With over 1,800 engineers, MAQ Software has globally integrated teams in Redmond, Washington; Plano, Texas; and Noida, Mumbai, and Hyderabad, India, delivering solutions with increased velocity and tech intensity. Our daily delivery and feedback model offers the flexibility to adapt solutions to changing business needs.
MAQ Software's dedication to customer success has led to sustained growth. Inc. magazine has recognized MAQ Software for sustained organic growth by listing us on the Inc. 5000 list twelve times -a rare honor.
Engineering culture
At MAQ Software, we foster a strong engineering culture with a can-do attitude. Our key managers come from excellent educational backgrounds and have significant experience in growing a company and mentoring software engineers. Due to our smaller size, we are agile and able to adopt the latest technologies and computing trends ahead of larger industry players.
As a part of our globally distributed engineering team, our engineers gain exposure to the latest software engineering practices and fast development cycles, providing them with the opportunity to work on challenging technical problems that utilize cutting-edge technologies for fast-paced software delivery. Our collaborative and supportive work environment encourages innovation and growth, making our company an exciting and rewarding place to work.
Examples of our projects:
  • We built an agentic AI solution that redefined event information access for a global technology leader, delivering instant, accurate answers to attendee questions at scale. Using Azure OpenAI Service, Azure AI Search, and Azure Machine Learning, combined with Retrieval-Augmented Generation (RAG), we engineered a secure, multilingual Copilot platform capable of processing data from 22 file formats across multiple sources. Our team leveraged Azure Databricks for advanced data transformation, Azure Front Door for global load balancing, and Microsoft Entra ID with Azure Key Vault for enterprise-grade security. The result: a system that served over 200,000 users, handled millions of interactions, and reduced support requests by 70%, setting a new benchmark for scalable, intelligent, and personalized event experiences.
  • We built a high-performance reporting solution that redefined data refresh efficiency for a leading office supply retailer, delivering near real-time insights and dramatically faster report access. By integrating Snowflake-managed Iceberg tables into Microsoft Fabric via OneLake shortcuts and leveraging Power BI's Direct Lake mode, we built a scalable architecture that eliminated data duplication and significantly reduced latency. Our team leveraged Azure Data Lake Storage for external volume dumps, semantic modeling for streamlined analytics, and Fabric F256 SKU with autoscale for optimized compute. The result: report load times dropped by 80%, refresh cycles shrank from 10 days to minutes, and infrastructure costs fell by 60%, setting a new benchmark for enterprise-grade reporting performance.
  • We helped a global industrial technology leader transform its construction operations by replacing a fragmented, batch-based ERP system with a real-time intelligence solution built on Microsoft Fabric. The previous setup-based on Databricks and Snowflake-struggled with delayed data updates, high maintenance, and siloed systems. By implementing Microsoft Fabric's Real-Time Intelligence capabilities, including Eventstreams, Reflex, and Power BI dashboards, we enabled real-time data ingestion, anomaly detection, and instant insights. The result: 20-30% cost savings, 50% less IT maintenance, and a 10x improvement in data latency. This empowered faster decision-making, proactive issue resolution, and a more agile, data-driven organization.
  • We helped a Fortune 500 office supply retailer modernize its reporting by migrating from MicroStrategy to Power BI. The legacy system was costly and inefficient, requiring over 150 duplicate reports and individual licenses for each user. Our solution consolidated these into just five dynamic Power BI reports, each customizable with bookmarks and filters. By leveraging Snowflake and Import Mode, we delivered a scalable semantic model and a user-friendly experience. The result: reduced license costs, faster reporting, and empowered business users with self-service analytics.
  • We built an AI-powered chatbot for a global manufacturer of industrial test and diagnostic equipment to improve access to project lifecycle management data. Using Azure OpenAI, Azure AI Search, and Azure App Service, the solution indexed documents from SharePoint-including PDFs, Excel files, and dynamic web pages-into a centralized, searchable interface. Power Automate and custom code streamlined data ingestion and processing, while Azure Cosmos DB stored historical interactions. The chatbot enabled employees to retrieve accurate insights quickly, reducing manual effort and improving decision-making. Post-deployment, the client achieved higher productivity, lower operational costs, and seamless access to project data through a single unified interface.

To read about some of our recent projects, visit https://maqsoftware.com/case-studies
Responsibilities
Analyze existing systems (30%)
  • Collect requirement specifications to analyze business processes and determine the exact nature of user's system requirements. Use tools like Microsoft 365 Copilot to summarize stakeholder input and map process flow from documents, emails, and meetings. Collaborate with module leaders and core team members to decide on system architecture.
  • Analyze existing system structures to identify opportunities for migration to cloud-based platforms. Use GitHub Copilot to assist in refactoring legacy code and Microsoft Azure AI services to evaluate cloud readiness and performance benchmarks.
  • Analyze user requirements and align them with available enterprise data sources to design solutions that deliver reliable performance and reasonable cost. Use tools such as GitHub Copilot to assist with query optimization and Azure DevOps MCP Server to validate data lineage and dependencies within project repositories.
  • Design processing steps and recommend system solutions based on user requirements, ensuring clarity and scalability.
Develop specifications and workflow (25%)
  • Prepare software specifications, flow charts, and process diagrams for software programmers to follow. Use GitHub Copilot to generate code templates and automate systems documentation such as design specifications, user manuals, technical manuals, descriptions of application operations, and methodology documentation.
  • Analyze feasibility using commercially available software systems (e.g., Microsoft Azure versus Amazon Web Services) and reporting systems (e.g., Power BI versus Tableau).
Analyze and verify implementation (25%)
  • Collaborate with systems analysts and programmers to develop data migration tools and define operational workflows for new systems.
  • Work with software developers to use GitHub Copilot for accelerating code development.
  • Set up the test environment, use GitHub Copilot to generate test cases, and use Playwright MCP to automate testing and compare data from multiple sources to verify reports for end users.
Review implementation status and reporting (10%)
  • Participate in technical collaboration meetings and periodical reviews of implementation status.
  • Report weekly task plan to the project management team for implementation of custom software.
Training and certifications (10%)
  • Participate in technical training and complete relevant industry courses and certifications.
Qualifications
Undergraduate or graduate degree in Computer Science, Information Systems, Applied Computational Math Sciences, or related engineering discipline.
Benefits
  • Annual salary range ($85,000 - $120,000).
  • Comprehensive medical, dental and vision insurance with employee premiums paid in full.
  • 401(k) retirement plan (company match of 50%, up to 6% of your salary) and immediate vesting.
  • Paid time off (PTO) - up to 3 weeks per year.

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