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Manager Data Analytics Engineer Jobs in Oklahoma

$90K - $110K/yr

Position Summary The Analytics Engineer is responsible for owning the design, build, and ongoing ... Demonstrated ability to work independently, manage priorities, and take ownership of data products ...

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 ...

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 ...

S/he will have experience in the design, implementation, and management of health monitoring and ... Data Analytics and Visualization Specialist.pdf The position is contingent upon availability of ...

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 ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary The Opportunity As a Data Engineer - Manager, you will play a pivotal role in transforming raw data ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

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Manager Data Analytics Engineer information

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

AspectManager Data Analytics EngineerData Analytics Engineer
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often leadership experienceBachelor's or Master's in Data Science, Analytics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersDevelops data models, analyzes data, implements solutions
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprisesCommon in similar industries, often within data teams

The main difference is that a Manager Data Analytics Engineer oversees teams and projects, focusing on leadership and strategic planning, while a Data Analytics Engineer primarily develops and implements data solutions. Both roles require strong technical skills, but the manager role adds a layer of team management and stakeholder communication.

How does a Manager Data Analytics Engineer typically balance technical project work with team leadership responsibilities?

As a Manager Data Analytics Engineer, you are expected to split your time between overseeing complex analytics engineering tasks and guiding your team’s development. This involves setting project priorities, conducting code reviews, and ensuring data solutions align with business goals, while also mentoring team members and facilitating collaboration with stakeholders like data scientists and business analysts. Successful managers often establish clear communication channels and delegate tasks effectively, so they can stay hands-on with key projects while supporting the professional growth of their team.

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

To thrive as a Manager Data Analytics Engineer, you need a strong background in data engineering, analytics, and leadership, typically with a degree in computer science or a related field. Familiarity with tools like SQL, Python, data warehousing platforms (e.g., Snowflake, Redshift), and certifications in cloud technologies or data management are common requirements. Excellent communication, problem-solving, and team management skills set top performers apart in this role. These competencies are essential for driving data strategy, ensuring data quality, and leading analytics teams to deliver actionable business insights.

What is a Manager Data Analytics Engineer?

A Manager Data Analytics Engineer is a professional who leads a team of data analytics engineers responsible for designing, building, and maintaining data systems and analytics solutions. They oversee data pipeline development, ensure data quality, and collaborate with stakeholders to translate business requirements into technical solutions. In addition to technical expertise, they manage project timelines, mentor team members, and help drive data-driven decision-making across the organization.
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 Manager Data Analytics Engineer jobs in Oklahoma? For Manager Data Analytics Engineer jobs in Oklahoma, the most frequently searched job titles are:
What job categories do people searching Manager Data Analytics Engineer jobs in Oklahoma look for? The top searched job categories for Manager Data Analytics Engineer jobs in Oklahoma are:
What cities in Oklahoma are hiring for Manager Data Analytics Engineer jobs? Cities in Oklahoma with the most Manager Data Analytics Engineer job openings:
Analytics Engineer

$90K - $110K/yr

Other

Posted 7 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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