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Senior Databricks Data Engineer Jobs in Oregon (NOW HIRING)

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager ... Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data ...

$114.40K - $137.40K/yr

KeyLogic is seeking Databricks Engineers to join our growing team supporting the Department of ... As a Data Engineer in this role, you will be responsible for designing, building, and maintaining ...

Senior Data Engineer

OR · Remote

$120K - $160K/yr

... team as a Senior Data Engineer . In this pivotal role, you will be responsible for designing ... The ideal candidate will bring deep expertise in Databricks, SQL, and modern data engineering ...

3663 Sr. Data Engineer

Portland, OR · On-site

$121.40K - $145.80K/yr

They are seeking a Senior Data Engineer to design and build modern cloud data platforms and ... Build and maintain Databricks-based data engineering solutions, including ingestion pipelines ...

New

OR · On-site

$85K - $141K/yr

Design, develop, and maintain end-to-end data pipelines using Databricks (Spark, PySpark, SQL) to ... Engineer and optimize data models, Delta tables, and curated datasets to support financial ...

OR

$114.40K - $137.40K/yr

We are looking for a Senior Data Engineer to help evolve and scale our modern data ecosystem ... Expertise with Databricks and other cloud data warehousing solutions such as S3, Redshift, or ...

$114.40K - $137.40K/yr

As a national leader in value-based care, we offer senior living communities and skilled nursing ... Support data platform tools such as Azure Data Factory, Databricks, Python/Spark jobs, and version ...

OR · On-site

$105.90K - $143.90K/yr

We are looking for a Senior Data Engineer* to join our team to ensure the accuracy and scalability ... or Databricks, and orchestrate workflows with tools like Dagster or Airflow * You write expert SQL ...

... Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies that meet the current and future business needs - Developing and documenting data ...

OR

$111.57K/yr

Data Engineer needed for Planet Equity Group located in Westlake, OH. Perform data engineering ... Synapse, Databricks, tabular cubes. Will provide services to client located through the U.S.

OR

$150K - $190K/yr

As a Sr. Software Engineer - Data, you will work with customers and internal stakeholders to ... Hands-on experience with Databricks * Hands-on experience with PowerBI report development * Hands ...

OR

$150K - $175K/yr

Job Summary The Lead Data Engineer will play a key role in engineering the enterprise data platform on Databricks, building scalable pipelines and transformation frameworks that support enterprise ...

Senior Data Engineer

OR · Remote

$105.90K - $143.90K/yr

About the Role As a Senior Data Engineer focused on AI/ML , you'll architect, build, and operate ... Experience with Data Lake/Lakehouse architectures (e.g., Databricks, Snowflake, Delta Lake) and ...

Data Engineer

Beaverton, OR · On-site

$119.10K - $143.10K/yr

Databricks AWS Apache Spark Python PySpark Previous Clients experience a plus. Any ETWs let go at the end of 05/31 can be considered since a 90 day break would be fulfilled. Skills Data engineer ...

Data Engineer

Beaverton, OR · Hybrid

$120.90K - $145.20K/yr

Databricks AWS Apache Spark Python PySpark Previous Clients experience a plus. Any ETWs let go at the end of 05/31 can be considered since a 90 day break would be fulfilled. Skills Data engineer ...

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Senior Databricks Data Engineer information

What are the key skills and qualifications needed to thrive as a Senior Databricks Data Engineer, and why are they important?

To thrive as a Senior Databricks Data Engineer, you need advanced expertise in data engineering concepts, big data technologies, and proficiency in programming languages like Python or Scala, usually backed by a bachelor's degree in computer science or a related field. Familiarity with Databricks, Apache Spark, cloud platforms (Azure, AWS, or GCP), and certifications like Databricks Certified Data Engineer are typically required. Strong problem-solving skills, effective communication, and the ability to collaborate across teams distinguish top performers in this role. These skills are essential to efficiently design scalable data solutions, optimize data workflows, and drive business insights in complex data environments.

How does a Senior Databricks Data Engineer typically collaborate with data scientists and analysts on large-scale projects?

A Senior Databricks Data Engineer works closely with data scientists and analysts to design, build, and optimize data pipelines that enable advanced analytics and machine learning initiatives. They often participate in cross-functional meetings to understand data requirements, translate them into scalable ETL processes, and ensure data quality and accessibility. Regular collaboration also involves troubleshooting data issues, optimizing Spark jobs for performance, and sharing best practices for data management. This close teamwork ensures that analytical teams have reliable, timely, and well-structured data to drive insights and decision-making.

What are Senior Databricks Data Engineers?

Senior Databricks Data Engineers are experienced professionals who design, develop, and optimize large-scale data processing pipelines using the Databricks platform. They work with big data technologies like Apache Spark, Delta Lake, and cloud platforms such as Azure or AWS. Their responsibilities include building and maintaining ETL processes, ensuring data quality, and collaborating with data scientists and analysts to deliver reliable, high-performance data solutions. As senior engineers, they also mentor junior team members and contribute to architectural decisions.

What is the difference between Senior Databricks Data Engineer vs Data Engineer?

AspectSenior Databricks Data EngineerData Engineer
CredentialsTypically requires experience with Databricks, Spark, cloud platforms, and often certifications like Databricks Certified Data Engineer AssociateRequires knowledge of data pipelines, SQL, ETL tools, and often cloud platform experience, but less specialized in Databricks
Work EnvironmentWorks primarily within Databricks environment, focusing on big data processing and analyticsWorks across various data tools and platforms, including traditional ETL and cloud services
Industry UsageCommon in organizations leveraging Databricks for big data analytics and machine learningWidely used across industries for general data pipeline development and data management

The main difference is that a Senior Databricks Data Engineer specializes in using Databricks and Spark for big data solutions, often requiring specific certifications and experience. A Data Engineer has a broader focus on data pipeline development across various tools and platforms, with less emphasis on Databricks-specific skills.

What are the most commonly searched types of Databricks Data Engineer jobs in Oregon? The most popular types of Databricks Data Engineer jobs in Oregon are:
What are popular job titles related to Senior Databricks Data Engineer jobs in Oregon? For Senior Databricks Data Engineer jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Senior Databricks Data Engineer jobs in Oregon look for? The top searched job categories for Senior Databricks Data Engineer jobs in Oregon are:
What cities in Oregon are hiring for Senior Databricks Data Engineer jobs? Cities in Oregon with the most Senior Databricks Data Engineer job openings:
Senior Forward Deployed Engineer - Databricks

Senior Forward Deployed Engineer - Databricks

Deloitte

Portland, OR

$110.80K - $152.20K/yr

Other

Posted 13 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

59th of 138 rated financial services


Job description

At Deloitte, Senior Forward Deployed Engineers (SFDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on September 30, 2026

Work you'll do

As a Senior Databricks FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include: 

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.
  • Coach client teams and end users on platform capabilities and AI enablement, while building trusted relationships, managing expectations, and supporting long-term engagement success.
  • Drive end-to-end sales and delivery support by developing demos/POCs, contributing to proposals and orals, articulating business value, and documenting solutions for smooth client handoff and knowledge transfer.
  • Strengthen team and organizational impact by mentoring other FDEs through design/code reviews and feedback, while contributing reusable components to intellectual capital.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Databricks including hands on experience with one of the following key platform technologies; DBRX, MLflow, Vector Search, Databricks AI Gateway
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code o
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

At Deloitte, Senior Forward Deployed Engineers (SFDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on September 30, 2026

Work you'll do

As a Senior Databricks FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include: 

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.
  • Coach client teams and end users on platform capabilities and AI enablement, while building trusted relationships, managing expectations, and supporting long-term engagement success.
  • Drive end-to-end sales and delivery support by developing demos/POCs, contributing to proposals and orals, articulating business value, and documenting solutions for smooth client handoff and knowledge transfer.
  • Strengthen team and organizational impact by mentoring other FDEs through design/code reviews and feedback, while contributing reusable components to intellectual capital.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Databricks including hands on experience with one of the following key platform technologies; DBRX, MLflow, Vector Search, Databricks AI Gateway
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code o
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

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