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Director Data Analytics Engineer Jobs in Oregon (NOW HIRING)

Sr. Data Engineer

OR · On-site +1

$100K - $150K/yr

  • Retirement

  • PTO

As an accomplished data engineer joining the Data & Analytics team, this is a terrific opportunity to become part of a fast-growing, revolutionary fintech company shaping the future of retail futures ...

Director, Data Architecture Location: United States (Remote) Interested applicants must reside in ... Coach and enable engineers and analysts on architecture expectations and best practices through ...

Analytics Engineer 5 - Ads Measurement DSE

OR · On-site +1

$330K - $566K/yr

  • Medical

  • Life

  • Retirement

  • PTO

As a Senior Analytics Engineer, you'll design metrics, generate insights by scoping and executing ... Analyze and interpret data to understand and provide recommendations for the effectiveness of ...

Data Engineer - Senior Associate

Portland, OR · On-site

$77K - $202K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship ...

Analytics Engineer 5 - Content & Studio

OR · On-site +1

$330K - $566K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Data and Insights at Netflix is aimed at using data, analytics, causal inference, machine learning ... We are looking for a Senior Analytics Engineer to lead the design and implementation of robust data ...

Sr. Data Analyst - Finance

OR · On-site +1

$120K - $130K/yr

Analytics Engineering & BI: Experience with modern data stacks including cloud-based databases. Hands on experience with data warehousing tools (e.g., Snowflake, BigQuery, Redshift). Experience with ...

Data Engineer - Manager

Portland, OR · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship ...

... analytics capabilities, creating epics, user stories, and other assets for architects and engineers ... Act as the key interface between business stakeholders (including director level and above) and ...

... analytics capabilities, creating epics, user stories, and other assets for architects and engineers ... Act as the key interface between business stakeholders (including director level and above) and ...

... direct and indirect operating costs, including hardware, subscriptions, and service contracts ... Data Analytics, Supply Chain, Engineering, or related field - 3-5 years of experience in data ...

... Data Scientist to Join our Team in a Remote capacity. At ICI Services, our employee-owners drive ... Our diverse team of acquisition experts, financial analysts, engineers, logisticians, IT ...

Showing results 41-60

Director Data Analytics Engineer information

What does a Director Data Analytics Engineer do?

A Director Data Analytics Engineer oversees the design, development, and implementation of data analytics solutions within an organization. They lead teams of data engineers and analysts, set the vision for data infrastructure, and ensure that data systems effectively support business goals. Their responsibilities include managing data architecture, optimizing data workflows, and collaborating with other departments to translate business needs into technical requirements. Additionally, they are often involved in strategic planning and in establishing best practices for data governance and security.

What are the key skills and qualifications needed to thrive as a Director Data Analytics Engineer?

To thrive as a Director Data Analytics Engineer, you need deep expertise in data engineering, analytics, and strategic leadership, supported by a degree in computer science or a related field and significant industry experience. Proficiency with big data platforms (such as Hadoop and Spark), cloud services (AWS, Azure, or Google Cloud), and advanced analytics tools, along with certifications in data management or analytics, is typically required. Exceptional communication, team leadership, and problem-solving skills help drive cross-functional collaboration and innovation. These skills and qualities are essential for effectively leading analytics initiatives, translating business needs into data solutions, and driving organizational growth through data-driven decision-making.

How does a Director Data Analytics Engineer typically collaborate with cross-functional teams to drive data-driven decision making?

As a Director Data Analytics Engineer, you will regularly collaborate with stakeholders across business units, such as product managers, IT, and executive leadership, to understand their data needs and translate them into actionable analytics solutions. This often involves leading a team of data engineers and analysts, facilitating regular meetings to align on project priorities, and ensuring data infrastructure supports strategic business objectives. Effective communication and the ability to present complex technical findings in a clear, business-friendly manner are essential for fostering a data-driven culture and influencing key decisions.

What is the difference between Director Data Analytics Engineer vs Data Analytics Manager?

AspectDirector Data Analytics EngineerData Analytics Manager
CredentialsBachelor's/Master's in Data Science, Analytics, or related field; often requires leadership experienceBachelor's/Master's in Analytics, Business, or related field; focus on team management
Work EnvironmentStrategic leadership, overseeing analytics projects, collaborating with executivesManaging analytics teams, project execution, reporting to directors or executives
Industry UsageUsed across tech, finance, healthcare, and more for high-level analytics strategyCommon in various industries for managing analytics operations

The Director Data Analytics Engineer focuses on strategic leadership and overseeing analytics engineering initiatives, while the Data Analytics Manager handles day-to-day team management and project execution. Both roles require strong technical backgrounds, but the director position emphasizes strategic planning and cross-department collaboration.

What are the most commonly searched types of Data Analytics Engineer jobs in Oregon?

The most popular types of Data Analytics Engineer jobs in Oregon are:

What cities in Oregon are hiring for Director Data Analytics Engineer jobs?

Cities in Oregon with the most Director Data Analytics Engineer job openings:

Infographic showing various Director Data Analytics Engineer job openings in Oregon as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Sr. Data Engineer

NinjaTrader

OR • On-site, Remote

$100K - $150K/yr

Full-time

Retirement, PTO

Re-posted 23 days ago


Job description

What you'll do:

Your data-driven mindset and ability to work with large-scale data systems enable NinjaTrader to serve customers better, identify new opportunities, and improve processes. As an accomplished data engineer joining the Data & Analytics team, this is a terrific opportunity to become part of a fast-growing, revolutionary fintech company shaping the future of retail futures trading.

At NinjaTrader, you'll play a key role in designing and operationalizing the modern data platform that powers our analytics, trading tools, and AI initiatives. This role is remote-friendly and reports to the Manager, Data & Analytics Engineering.

As a Sr. Data Engineer, your primary responsibility is to stay one step ahead of your fellow team members by providing the platform, tools, and infrastructure they need to deliver deployable solutions to real-world business problems. This goes beyond maintaining pipelines-it's about delivering best-in-class data architecture, scalable workflows, and real-time solutions that power trading, product development, and machine learning.

In this role you will:

  • Design, build, and maintain robust data pipelines and data lake architecture for both batch and real-time streaming use cases, including high-volume, low-latency data processing
  • Improve observability, alerting, and SLOs across data systems so pipelines are easier to monitor and issues are caught early
  • Optimize ETL/ELT workflows for performance, scalability, and fault tolerance
  • Develop dbt workflows to onboard Evaluation Partners and create end-of-day reporting for partner analysis
  • Build and support event-driven architectures and scalable platform components
  • Contribute to the orchestration and automation of workflows
  • Integrate complex financial APIs and third-party data sources into internal systems
  • Collaborate with analytics, product, and ML engineers to develop and deploy reliable data products
  • Work on feature pipelines and model-ready data to support ML engineers
  • Promote high standards in code quality, testing, and platform reliability
  • Participate in Agile ceremonies and foster a collaborative, growth-oriented team culture

What you'll need:

  • Bachelor's degree in Computer Science, Engineering, or a related field
  • 5+ years of experience in data engineering, platform engineering, or backend development
  • Strong skills in SQL and Python for building and testing data solutions
  • Hands-on experience with GCP and GCP data products (BigQuery, Cloud SQL, Cloud Storage, etc.)
  • Experience with AWS cloud services (S3, Glue, Athena, Kinesis) in addition to GCP; bonus for EMR
  • Experience with CI/CD pipelines, infrastructure-as-code, and version-controlled deployment workflows (e.g., Terraform, GitOps)
  • Hands-on dbt experience building and maintaining dbt projects (models, tests, macros, documentation, CI)
  • Proficiency with workflow orchestration tools (e.g., Airflow, Prefect)
  • Knowledge of data lake architecture, including file formats (Parquet, Avro) and open table formats (Apache Iceberg)
  • Familiarity with event-driven and service-oriented architecture
  • A track record of building automated, well-tested, and observable data systems
  • Comfortable working both independently and collaboratively in a fast-paced Agile environment

Bonus points for:

  • Hands-on Kubernetes experience, especially around data workloads and containerized pipelines
  • Experience with streaming technologies (e.g., Kafka, Spark Streaming, Flink) and comfort working with high-volume, low-latency data flows
  • Experience with change data capture tools (e.g., Debezium, Kafka Connect) and real-time data integration patterns
  • Experience with BI tools like Looker Studio or QuickSight
  • Experience with observability and monitoring tooling (e.g., Datadog, Grafana, Prometheus)
  • Background in fintech, trading, or derivatives

Compensation:

The salary range for this role will be $100,000.00 - $150,000.00 USD. In addition, this position will also receive an annual target bonus of 10%. Bonus pay at NinjaTrader is based on individual performance (50%) as well as company/team performance (50%).

Salary and bonus earnings are only two components of the total compensation package offered by NinjaTrader. NinjaTrader offers a 401K plan through ADP under which the company will match up to 3.5% of employee contributions. Annual paid time off allowance accrues at a rate of 18 days per year (some positions may qualify for more) plus seven paid holidays.

Location:

This role is based in Chicago, IL.* We follow a hybrid work schedule: In-office Tuesday through Thursday, with remote work on Mondays and Fridays. In addition to these weekly remote days, we offer:

  • 20 additional flex remote days annually

  • 5 Company Wide Office-Optional weeks tied to major holidays


*There may be remote flexibility for exceptional candidates in the following states: California, Colorado, Florida, Georgia, Illinois (outside the Chicago area), Indiana, Minnesota, Missouri, Montana, New Jersey, New York, North Carolina, Ohio, Oregon, Pennsylvania, South Carolina, Texas, Utah, Vermont, Virginia, Washington, Washington DC, Wisconsin.