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Data Analytics Jobs in Cleveland, TX (NOW HIRING)

DEXTER TECHNOLOGIES INC

Data Analytics Engineer

Houston, TX · On-site

$130K - $140K/yr

Data Analytics Engineer Location: Houston TX (4 days in office) Type: Full Time This role is a hybrid, bridging the gap between data engineering and business intelligence. You'll spend part of your ...

New

McKesson

Manager, Data Analytics

The Woodlands, TX

Manager, Data Analytics We're looking for someone who can sit between the business and the technical side and thrive in both. Our Generics organization is going through a period of significant change ...

MCKESSON

Manager, Data Analytics

The Woodlands, TX

Manager, Data Analytics We're looking for someone who can sit between the business and the technical side and thrive in both. Our Generics organization is going through a period of significant change ...

McKesson

Manager, Data Analytics

The Woodlands, TX

Manager, Data Analytics We're looking for someone who can sit between the business and the technical side and thrive in both. Our Generics organization is going through a period of significant change ...

TestingXperts

Big Data Analytics Process

Houston, TX · On-site

Big Data Analytics Process Location: Houston, TX Must Have Skills (Top 2 technical skills only) Minimum 8 years of relevant experience in applying data mining, artificial intelligence, signal ...

Hp

Senior AI & Data Analytics

Spring, TX

$116K - $182K/yr

Senior AI & Data Analytics Description - Job Summary This role is responsible for overseeing the delivery of very large, complex internal projects, which often span multiple regions, and involve high ...

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All JobsData Analytics JobsData Analytics Jobs in Cleveland, TX

Data Analytics information

See Cleveland, TX salary details

$22

$49

$85

How much do data analytics jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for data analytics in Cleveland, TX is $49.44, according to ZipRecruiter salary data. Most workers in this role earn between $39.71 and $56.01 per hour, depending on experience, location, and employer.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

How does a data analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

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

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

Is a data analyst still a good career?

Data analysts remain in high demand across industries due to the increasing reliance on data-driven decision making. Strong skills in tools like Excel, SQL, and visualization software, along with certifications, can enhance job prospects and career growth in this field.

What jobs can a data analyst do?

A data analyst can work in roles such as business analyst, data scientist, data engineer, or reporting specialist. They analyze data to help organizations make informed decisions, often using tools like Excel, SQL, and visualization software, and may require knowledge of statistical methods and programming languages like Python or R.

What kind of jobs can you get with data analytics?

Data analytics skills can lead to roles such as data analyst, business analyst, data scientist, and data engineer. These jobs involve analyzing data to support decision-making, often requiring proficiency in tools like Excel, SQL, and Python, and may require relevant certifications or a strong understanding of statistical methods.

What are popular job titles related to Data Analytics jobs in Cleveland, TX?

For Data Analytics jobs in Cleveland, TX, the most frequently searched job titles are:

What cities near Cleveland, TX are hiring for Data Analytics jobs?

Cities near Cleveland, TX with the most Data Analytics job openings:

Data Analytics jobs near you
Infographic showing various Data Analytics job openings in Cleveland, TX as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 11% Part Time, and 7% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $102,827 per year, or $49.4 per hour.

Data Analytics Engineer

DEXTER TECHNOLOGIES INC

Houston, TX • On-site

$130K - $140K/yr

Full-time

Medical, Dental, Vision

Posted 3 days ago

New

Job description

Benefits:
  • Dental insurance
  • Health insurance
  • Vision insurance

Hi,
We are actively seeking qualified candidates for the following position for our client, who is an industry leader:
 
Data Analytics Engineer
Location: Houston TX (4 days in office)
Type: Full Time 
 
This role is a hybrid, bridging the gap between data engineering and business intelligence.  You'll spend part of your time writing and optimizing SQL — building staging tables, views, and fact/dimension models — and part of your time building semantic models and reports in Power BI. Keeping an eye on our scheduled data pipelines, you’ll handle first-line troubleshooting when something fails. You'll work closely with the Sr. Manager, Data & Analytics, and with business stakeholders across Finance, Operations, and other functions who depend on accurate, well-modeled data.
This is a great fit for someone who wants breadth — real ownership across the data stack — on a team small enough that your work visibly matters.
 
Key Responsibilities
·       Data modeling & SQL: Design, build, and maintain SQL views, staging tables, and fact/dimension models in our Azure SQL data warehouse, including deduplication and business-rule logic (e.g., status-based routing, multi-source reconciliation).
·       Semantic models & reporting: Build and maintain Power BI semantic models — relationships, DAX measures, security roles — and the reports and dashboards built on top of them for business stakeholders and company-wide reporting.
·       Pipeline support: Share responsibility with the Sr. Manager, Data & Analytics for monitoring scheduled Azure Data Factory pipelines and Power BI dataset refreshes. Respond to failures and perform basic troubleshooting.
·       Pipeline modifications: Make minor modifications to existing pipelines to support new or changing business requirements, as your familiarity with the tooling grows. 
·       Business partnership: Partner with business SMEs to translate reporting requests and business logic (commission structures, revenue recognition, inventory rules, etc.) into accurate, well-documented data models.
·       Documentation: Write and maintain documentation for data models, metric definitions, and report logic so that data lineage and ownership are clear beyond any one person.
·       Standards & quality: Follow and help evolve team standards for naming conventions, DAX style, and semantic model design as the team's practices mature.
  • Continuous Improvement: Proactively identify opportunities for process improvements, optimize current data workflows, and incorporate new technologies or tools to enhance data analytics capabilities.
Knowledge and Skills  
Required
·       3+ years in a data-focused role (analytics engineer, BI developer, data analyst, or similar) with hands-on SQL work — comfortable with CTEs, window functions, and reading/writing complex, multi-source views.
·       Solid Power BI experience beyond report formatting — you've built semantic models from scratch and written DAX involving CALCULATE, filter context, and context transition, not just basic aggregations.
·       Dimensional modeling fundamentals (star schemas, slowly changing dimensions).
·       A track record of working directly with business stakeholders to translate ambiguous requirements or business rules into a working data model.
·       Strong attention to detail with data integrity — you double-check your joins and know how a bad join or an inclusive date boundary can quietly break a report.
Preferred
·       Exposure to an ERP or other core business system as a data source (order, invoicing, or GL data) -  you understand that business rules, not just dates, often drive how records should be deduplicated or classified.
·       Understanding of ETL/ELT concepts and working knowledge of orchestration tools like Azure Data Factory or similar tools for automating data pipelines.
·       Familiarity with Microsoft Fabric Administration and Environment (Lakehouses, Dataflows Gen2) — not required, but a plus given our platform direction.
·       Basic Git / source control experience.
·       Python for data tasks.
  • Knowledge of data quality frameworks and data governance practices. 
Qualifications
  • Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field. Master’s degree is a plus.
  • 3+ years in a data-focused role (analytics engineer, BI developer, data analyst, or similar) with hands-on SQL work — comfortable with CTEs, window functions, and reading/writing complex, multi-source views.

Flexible work from home options available.