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Data Analytics Engineer Jobs in Oklahoma (NOW HIRING)

$90K - $110K/yr

Position Summary The Analytics Engineer is responsible for owning the design, build, and ongoing ... This role creates and evolves foundational and business data products from governed underlying data ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced ...

Data and Analytics AI Engineer

Tulsa, OK · On-site

$104K - $125K/yr

The Data and Analytics AI Engineer is responsible for designing, building, and supporting enterprise data, analytics, automation, and artificial intelligence solutions that enable business growth and ...

Data and Analytics AI Engineer

Tulsa, OK

$104K - $125K/yr

The Data and Analytics AI Engineer is responsible for designing, building, and supporting enterprise data, analytics, automation, and artificial intelligence solutions that enable business growth and ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and ...

You'll report directly to our Director of Data Engineering and Advanced Analytics and play a hands-on role in shaping how a leading electrical contractor turns data into a competitive advantage. WHAT ...

Data Engineer II

Tulsa, OK · On-site

$120/hr

Data Engineer II/III Location: Tulsa, Oklahoma Salary: $120-135k Position is not eligible for ... Connect to and analyze data from a variety of source systems to assess data quality, structure, and ...

Data Engineer II

Tulsa, OK · On-site

$120/hr

Data Engineer II/III Location: Tulsa, Oklahoma Salary: $120-135k Position is not eligible for ... Connect to and analyze data from a variety of source systems to assess data quality, structure, and ...

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Showing results 1-20

Data Analytics Engineer information

See Oklahoma salary details

$41.1K

$119.8K

$163.9K

How much do data analytics engineer jobs pay per year?

As of Aug 5, 2026, the average yearly pay for data analytics engineer in Oklahoma is $119,772.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,700.00 and $127,000.00 per year, depending on experience, location, and employer.

How do data analytics engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

What are the key skills and qualifications needed to thrive as a data analytics engineer, and why are they important?

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

What is the difference between Data Analytics Engineer vs Data Scientist?

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What are the most commonly searched types of Data Analytics Engineer jobs in Oklahoma? The most popular types of Data Analytics Engineer jobs in Oklahoma are:
What are popular job titles related to Data Analytics Engineer jobs in Oklahoma? For Data Analytics Engineer jobs in Oklahoma, the most frequently searched job titles are:
Infographic showing various Data Analytics Engineer job openings in Oklahoma as of July 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $119,772 per year, or $57.6 per hour.

$90K - $110K/yr

Other

Posted 27 days ago


Job description

Position Summary

The Analytics Engineer is responsible for owning the design, build, and ongoing maintenance of data products in the MART layer of the firm's data platform. This role creates and evolves foundational and business data products from governed underlying data, applying reusable business logic, documentation, testing, and access controls so data can be consumed consistently across the enterprise. The ideal candidate also authors and maintains semantic models that make trusted data easier to use for AI experiences, dashboards, reporting, and downstream integrations into operational platforms. Success in this role requires strong technical depth, a product mindset, and close partnership with engineering, BI, analytics, and business stakeholders.

This is a hybrid role with 3 days/week onsite in St. Louis.

Primary Responsibilities

  • Own the design, development, and maintenance of MART-layer foundational and business data products built from curated enterprise data.

  • Translate business requirements into reusable data products, metrics, and transformation logic that support consistent consumption across teams and platforms.

  • Build and maintain semantic models with rich metadata, business definitions, and synonyms to enable trusted self-service analytics and AI consumption.

  • Develop models that support multiple consumption patterns, including dashboards, reports, AI agents, APIs, file delivery, and operational system integrations.

  • Apply complex business logic in a governed, version-controlled manner using modern transformation tooling and software engineering best practices.

  • Partner with data engineers, BI engineers, analysts, architects, and business stakeholders to define product intent, validate logic, and prioritize enhancements.

  • Ensure data product quality through testing, monitoring, reconciliation, and issue resolution across upstream data, transformations, and downstream consumption.

  • Document data products, semantic models, lineage, and usage guidance to improve transparency, stewardship, and user adoption.

  • Support governed access patterns through metadata, role-based access considerations, and alignment with enterprise data governance standards.

  • Continuously improve MART-layer patterns, semantic model design, and consumer enablement based on platform evolution and business needs.

Required Skills

  • Strong experience building analytics-ready data models and reusable business logic in modern cloud data platforms such as Snowflake.

  • Hands-on expertise with DBT or similar transformation frameworks, including modular modeling, testing, documentation, and version control.

  • Proven ability to design and maintain semantic models, metrics, dimensions, and business definitions for consistent downstream consumption.

  • Strong SQL skills and experience optimizing transformation logic for performance, scalability, and maintainability.

  • Experience supporting multiple data consumption patterns, including BI dashboards, AI use cases, reporting, APIs, file delivery, and operational integrations.

  • Understanding of data governance, metadata, lineage, role-based access, and quality controls in enterprise data platforms.

  • Ability to partner effectively with cross-functional stakeholders to translate business needs into scalable, trusted data products.

  • Strong written and verbal communication skills with the ability to document logic, definitions, assumptions, and usage guidance clearly.

Qualifications

  • Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field, or equivalent practical experience.

  • 5+ years of experience in analytics engineering, data engineering, BI engineering, or a closely related data role.

  • Experience building governed data models and data products in enterprise environments with multiple downstream consumers.

  • Demonstrated experience applying software engineering best practices to analytics workflows, including Git-based development, testing, and deployment discipline.

  • Experience working with modern BI and semantic technologies such as Power BI, Snowflake semantic capabilities, or similar platforms is preferred.

  • Familiarity with metadata/catalog platforms, lineage tooling, and enterprise documentation practices is preferred.

  • Experience in financial services, wealth management, or other regulated industries is a plus.

  • Demonstrated ability to work independently, manage priorities, and take ownership of data products from design through ongoing support.

This position is an exempt position. The annualized base pay range for this role is expected to be between $90,000 - $110,000.  Actual base pay could vary based on factors including but not limited to experience, subject matter expertise, geographic location where work will be performed and the applicant's skill set.  The base pay is just one component of the total compensation package for employees.  Other reward may include an annual cash bonus and a comprehensive benefits package.

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