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Analytics Engineer Jobs in Plano, TX (NOW HIRING)

Apex Systems

Senior Analytics Engineer

Southlake, TX · On-site

Job#: 3044565 Senior Analytics Engineer (Remote in S outhlake, TX or Lone Tree, CO ) The Senior Analytics Engineer is responsible for transforming complex data into trusted datasets, actionable ...

The LaSalle Group

Analytics Engineer

Fort Worth, TX · On-site

$60 - $70/hr

Our client is seeking an experienced Analytics Engineer to join its growing Data & Analytics team. This role is ideal for someone who enjoys solving business problems through data, partnering ...

Premier Truck Rental

Senior Analytics Engineer

Fort Worth, TX · On-site

$100K - $137K/yr

POSITION SUMMARY As a Senior Analytics Engineer , you will serve as the technical leader responsible for building and maintaining the transformation and semantic layer that powers enterprise-wide ...

Baker Botts Llp

Analytics Engineer

Dallas, TX · On-site

ABOUT THE ROLE Baker Botts is building its Enterprise Data Services team and is seeking an Analytics Engineer to help transform enterprise data into trusted, analytics-ready assets that support ...

Premier Truck Rental

Senior Analytics Engineer

Dallas, TX

$103K - $142K/yr

POSITION SUMMARY As a Senior Analytics Engineer , you will serve as the technical leader responsible for building and maintaining the transformation and semantic layer that powers enterprise-wide ...

Helenoftroy

Sr. AI Analytics Engineer

Dallas, TX · Hybrid

Senior AI Analytics Engineer Department: IT Work Location (s): * El Paso, TX * Plano, TX, * Arlington, TN, * Marlborough, MA. Hybrid Schedule: At Helen of Troy, we embrace a flexible hybrid work ...

3B Staffing LLC

Analytics Developer

Dallas, TX · Hybrid

Principal Analytics Engineer Location: Hybrid Duaration: 6+ months Details: * Enjoy co-designing new platform capabilities and workflows for platform engineering teams in support of new ways of ...

3B Staffing LLC

Analytics Developer

Dallas, TX · Hybrid

Principal Analytics Engineer Location: Hybrid Duaration: 6+ months Details: * Enjoy co-designing new platform capabilities and workflows for platform engineering teams in support of new ways of ...

Select Minds LLC

Predictive Analytics Engineer

Dallas, TX · On-site

$110 - $160/hr

Opportunity for advancement Data Scientist / Predictive Analytics Engineer Location: Dallas, TX (Hybrid, 3 days onsite per week) Employment Type: Full-Time / Contract (W2) Duration: Long-Term Work ...

Ericsson

Marketing Analytics Engineer

Plano, TX

About this opportunity We are looking for a Marketing Analytics Engineer to help build the next generation of marketing data, AI, and analytics capabilities. In this role, you'll strengthen the data ...

New

Select Minds LLC

Predictive Analytics Engineer

Dallas, TX · On-site

$100K - $120K/yr

Opportunity for advancement Data Scientist / Predictive Analytics Engineer Location: Dallas, TX (Hybrid, 3 days onsite per week) Employment Type: Full-Time / Contract (W2) Duration: Long-Term Work ...

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Showing results 1-20

All JobsAnalytics Engineer JobsAnalytics Engineer Jobs in Plano, TX

Analytics Engineer information

See Plano, TX salary details

$60.4K

$105.4K

$172K

How much do analytics engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for analytics engineer in Plano, TX is $105,441.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,740.00 and $118,352.00 per year, depending on experience, location, and employer.

What is an analytics engineer?

An Analytics Engineer is a professional who bridges the gap between data engineering and data analysis. They are responsible for designing, building, and maintaining data models, pipelines, and analytics tools that enable organizations to make data-driven decisions. Analytics Engineers often work closely with data analysts and business stakeholders to ensure clean, reliable, and well-structured data is available for reporting and analysis. Their work typically involves using SQL, data transformation tools like dbt, and cloud data warehouses to create scalable and efficient data solutions.

How does an analytics engineer typically collaborate with data scientists and business stakeholders on projects?

Analytics Engineers play a critical bridge role between data engineering and data analysis. They work closely with data scientists to transform raw data into clean, reliable datasets that are ready for advanced analytics or modeling. At the same time, they collaborate with business stakeholders to understand reporting needs, ensuring that data models align with business goals. Regular communication and iterative feedback are key, as Analytics Engineers often gather requirements, build data pipelines, and adjust data products based on stakeholder input.

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

To thrive as an Analytics Engineer, you need a strong foundation in data modeling, SQL, and analytics engineering principles, often supported by a degree in computer science, data science, or a related field. Proficiency with data transformation tools such as dbt, cloud data warehouses like Snowflake or BigQuery, and version control systems like Git is essential. Strong problem-solving skills, communication, and collaboration abilities help translate business needs into scalable data solutions and foster teamwork. These skills and qualities are crucial for ensuring data quality, building reliable analytics infrastructure, and enabling data-driven decision-making across organizations.

What is the difference between Analytics Engineer vs Data Engineer?

AspectAnalytics EngineerData Engineer
CredentialsOften requires SQL, Python, data modeling certificationsRequires similar skills, often with additional focus on infrastructure and systems
Work EnvironmentFocuses on data analysis, visualization, and reportingBuilds data pipelines, manages data infrastructure
Industry UsageCommon in analytics teams, BI, and data-driven rolesPrevalent in data engineering, data platform teams

While both roles work closely with data, Analytics Engineers primarily focus on transforming data for analysis and visualization, whereas Data Engineers build the infrastructure and pipelines that enable data access. Understanding these differences helps in choosing the right career path or job role.

Do analytics engineers make good money?

Analytics engineers typically earn competitive salaries that vary by experience, location, and industry. They often have skills in SQL, data modeling, and tools like Python or Spark, which can contribute to higher compensation. Overall, the role is considered well-paying within the data and analytics field.

What do analytics engineers do?

Analytics engineers design, build, and maintain data pipelines and infrastructure to enable data analysis and reporting. They work with tools like SQL, Python, and data warehouses to ensure data is accurate, accessible, and well-structured for business insights.

What are the most commonly searched types of Analytics Engineer jobs in Plano, TX?

The most popular types of Analytics Engineer jobs in Plano, TX are:

What are popular job titles related to Analytics Engineer jobs in Plano, TX?

For Analytics Engineer jobs in Plano, TX, the most frequently searched job titles are:

What job categories do people searching Analytics Engineer jobs in Plano, TX look for?

The top searched job categories for Analytics Engineer jobs in Plano, TX are:

What cities near Plano, TX are hiring for Analytics Engineer jobs?

Cities near Plano, TX with the most Analytics Engineer job openings:

Analytics Engineer jobs near you
Infographic showing various Analytics Engineer job openings in Plano, TX as of August 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $105,441 per year, or $50.7 per hour.

Analytics Engineer

BlueSky Resource Solutions

Dallas, TX • On-site

Other

Re-posted 2 days ago

Job description

The is a hybrid opportunity with 4-days onsite in Dallas, TX, Atlanta, GA, or Ashburn, VA. Candidates MUST be local to the one of these locations. This role is not open to C2C, OPT, or any Visa consideration. No vendor support of any kind allowed.



JOB DESCRIPTION

Core Job Requirements

  • 5+ years of experience in analytics engineering, data engineering, or advanced business intelligence roles within a modern data stack environment
  • Advanced proficiency in SQL with demonstrated experience building performance, well-modeled analytical datasets
  • Hands-on experience with dbt for analytics-layer modeling, testing, and documentation
  • Experience working with cloud data warehouses, preferably Snowflake, including performance tuning and cost-aware design
  • Strong understanding of analytics engineering best practices, including:
  • -Star and snowflake schemas
  • -Incremental models
  • -Fact / dimension separation
  • -Medallion Architecture
  • Experience working in a CI/CD-driven analytics environment, including version control, code review, and deployment pipeline
  • Proven ability to partner closely with business stakeholders to translate requirements into trusted analytical asset
  • Bachelor’s degree in Analytics, Information Systems, Computer Science, Mathematics, Finance, or equivalent practical experience


Technical & Platform Skills

  • Advanced SQL and data modeling expertise
  • dbt (models, tests, macros, docs, exposures)
  • Snowflake (query optimization, warehouse usage patterns, role-based access awareness)
  • Experience integrating data from SaaS systems using ELT tools (e.g., Fivetran, Stitch, etc.)
  • Familiarity with metadata management, data quality checks, and analytical lineage


Professional & Communication Skills

  • Strong business acumen with the ability to frame data in commercial terms
  • Clear, concise communicator capable of working with:
  • -Sales leadership
  • -Data engineering and platform teams
  • -Ability to write clear, durable documentation for models, metrics, and assumptions
  • High attention to detail with a strong bias toward accuracy, consistency, and auditability
  • Comfortable operating in a federated enterprise environment with multiple upstream systems



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