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Data Analytics Supervisor Jobs in Texas (NOW HIRING)

Requirements Supervisory Responsibilities: * Data Engineer(s) * Data Analysts/Business Analysts Duties/Responsibilities: * Lead and manage the Data Engineering & Analytics team, providing mentorship ...

New

Data Scientist

Plano, TX · On-site

$80K - $134K/yr

Overview PepsiCo Data & Analytics Overview: With data deeply embedded in our DNA, PepsiCo Data ... Qualifications * 3+ years' experience in Statistical/ML techniques to solve supervised (regression ...

Data Scientist

Plano, TX · On-site

$80K - $134K/yr

Overview PepsiCo Data & Analytics Overview: With data deeply embedded in our DNA, PepsiCo Data ... Qualifications * 3+ years' experience in Statistical/ML techniques to solve supervised (regression ...

Data Scientist

Plano, TX · On-site

$80.20 - $134.25/hr

Overview PepsiCo Data & Analytics Overview: With data deeply embedded in our DNA, PepsiCo Data ... Qualifications * 3+ years' experience in Statistical/ML techniques to solve supervised (regression ...

Overview PepsiCo Data & Analytics Overview: With data deeply embedded in our DNA, PepsiCo Data ... Qualifications * 3+ years' experience in Statistical/ML techniques to solve supervised (regression ...

Lead Data Analysis

Dallas, TX · On-site

$116K - $196K/yr

Supervisor: No TCP Career Step Differentiator: Manages complex data movement and storage from multiple sources, and high-level analytics to solve business problems. Education/Experience: Bachelor ...

This role combines data analytics, programming, and business intelligence with hands-on laboratory ... Notify supervisors promptly of unexpected test results and provide initial problem-solving with ...

Data analyst I

Austin, TX · On-site

$25 - $28/hr

1-3 years' experience in data analysis Strong Microsoft Excel skills (must-have) Experience with ... from supervisor, manager and/or more experienced colleagues. This position focuses on either ...

Lead Data Analysis

Dallas, TX · On-site

$116K - $196K/yr

Supervisor: No TCP Career Step Differentiator: Manages complex data movement and storage from multiple sources, and high-level analytics to solve business problems. Education/Experience: Bachelor ...

Lead Data Analysis

Dallas, TX · On-site

$116K - $196K/yr

Supervisor: No TCP Career Step Differentiator: Manages complex data movement and storage from multiple sources, and high-level analytics to solve business problems. Education/Experience: Bachelor ...

Experience in setting up supervised unsupervised learning ML/NLP models including data cleaning, data analytics, feature creation, model selection ensemble methods, performance metrics visualization

Data Scientist

Plano, TX · On-site

$110 - $150/hr

The majority of the role is hands‑on coding and analysis: writing SQL against a Snowflake data ... supervisory/management personnel, regardless of job title or routine job duties. #J-18808-Ljbffr

Data Scientist

Plano, TX · On-site

$105 - $150/hr

The majority of the role is hands‑on coding and analysis: writing SQL against a Snowflake data ... supervisory/management personnel, regardless of job title or routine job duties. #J-18808-Ljbffr

Data Scientist

Plano, TX · On-site

$90 - $140/hr

About the Role The Data Scientist is a technical analytics role supporting Finance, Operations ... supervisory/management personnel, regardless of job title or routine job duties. #J-18808-Ljbffr

Showing results 41-60

Data Analytics Supervisor information

What does a data analytics supervisor do?

A Data Analytics Supervisor oversees a team of data analysts, ensuring they collect, process, and analyze data effectively to support business decisions. They are responsible for managing projects, setting goals, and providing technical guidance to their team. Additionally, they collaborate with other departments to identify data needs, develop strategies, and present insights to leadership. The role requires strong analytical, communication, and leadership skills.

What are the key skills and qualifications needed to thrive as a data analytics supervisor?

To thrive as a Data Analytics Supervisor, you need strong analytical abilities, leadership experience, proficiency in statistical analysis, and a relevant degree in data science, statistics, or a related field. Familiarity with tools like SQL, Python, R, and business intelligence platforms (e.g., Tableau, Power BI) is typically required, along with experience managing data projects and teams. Excellent communication, problem-solving, and team management skills distinguish top performers in this role. These competencies are crucial for translating data insights into actionable strategies, guiding teams effectively, and ensuring the organization's data-driven decision-making success.

How does a data analytics supervisor typically collaborate with cross-functional teams within an organization?

A Data Analytics Supervisor often works closely with departments such as marketing, finance, operations, and IT to identify analytical needs and deliver actionable insights. They facilitate meetings to understand business objectives, translate requirements into data-driven solutions, and ensure that analytics projects align with broader organizational goals. Effective communication and the ability to translate complex data findings into clear, actionable recommendations are critical for fostering strong interdepartmental collaboration.

What is the difference between Data Analytics Supervisor vs Data Analyst?

AspectData Analytics SupervisorData Analyst
CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often requires experience in leadership rolesBachelor's degree in Data Science, Statistics, or related field; entry to mid-level experience
Work EnvironmentOversees teams, manages projects, collaborates with managementPerforms data analysis, reports findings, supports decision-making
Employer & Industry UsageUsed across industries like finance, healthcare, tech; common in organizations with analytics teamsFound in similar industries; often entry to mid-level role supporting analytics projects

The main difference is that Data Analytics Supervisors oversee teams and manage projects, while Data Analysts focus on analyzing data and generating reports. Supervisors typically have more experience and leadership responsibilities, whereas Data Analysts are more hands-on with data processing and analysis tasks.

What is the role of a data analytics supervisor?

A data analytics supervisor oversees data analysis teams, manages data collection and interpretation, and ensures accurate reporting to support business decisions. They often use tools like SQL, Excel, and data visualization software, and require strong leadership and analytical skills. The role involves coordinating projects, maintaining data quality, and implementing best practices in data management.

What are popular job titles related to Data Analytics Supervisor jobs in Texas?

For Data Analytics Supervisor jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Data Analytics Supervisor jobs in Texas look for?

The top searched job categories for Data Analytics Supervisor jobs in Texas are:

What cities in Texas are hiring for Data Analytics Supervisor jobs?

Cities in Texas with the most Data Analytics Supervisor job openings:

Infographic showing various Data Analytics Supervisor job openings in Texas as of August 2026, with employment types broken down into 20% Internship, and 80% Full Time. Highlights an 100% In-person job distribution.

Manager, Data Engineering & Analytics

Socket.dev

Dallas, TX • On-site

$170 - $230/hr

Other

Posted 2 days ago

New


Key responsibilities

  • Lead and manage the Data Engineering & Analytics team, providing mentorship, guidance, and support.

  • Design, implement, and maintain data products using modern technologies such as Python, SQL, dbt, Airflow, and BigQuery.

  • Own the team's intake, prioritization, and scheduling of data requests, ensuring clear communication with stakeholders.


Job description

Description Join our winning team, recently honored on Forbes' list ofAmerica’s Best Startup Employers!

THE HELPER BEES (THB) was created to fill an obvious need in an underserved community. Inspired by love and brought to reality through passion and determination, The Helper Bees was founded to empower older adult citizens and their families in their search for quality, affordable in-home care providers. We do this by providing older adults the ability to easily review, choose, and access affordable quality in-home helpers.

The Helper Bees mission is to be the best in the world at finding & fulfilling the needs of older adults.

At THB, we define our company culture through our Core Values:

  • Quickly iterate through solutions - We move at a fast pace which requires quick iterations to find a path to a repeatable solution
  • Seek ways to create immediate impact - Be thoughtful and proactive in how you make an impact on your team. Actively look for ways to make a fast, positive impact.
  • Bee the teammate you want to work with - We work as a team, help each other and encourage each other
  • Ask questions, answer questions - You can't iterate through solutions if you don't ask the right questions which is why there is an expectation that questions should be asked. When you know the answer, being a good teammate means chiming in to get others up to speed.
  • Take the time to celebrate wins - It's so easy for a team that is heads down to forget about all the great things they've accomplished. That's why we make it a priority to remind ourselves to create space to celebrate wins, big or small.
Job Summary:

As the Manager of Data Engineering & Analytics, you will report to the Vice President of Business Intelligence and lead The Helper Bees' Data Engineering and Analytics team, responsible for both the technical execution and strategic direction of data across the company. Your leadership will be key in ensuring the team produces accurate, governed, and on-time data reports, invoices, and analyses that our internal leaders and external partners depend on.
In this role, you will manage and develop a high-performing team of Data Engineers and Data Analysts, guiding their career growth, performance, and skill development. You will own how the team takes in, prioritizes, and delivers work, and you will set clear, achievable goals that ladder to the company's data objectives.
A central part of this role is helping the team move up the analytics maturity curve - from descriptive reporting toward **predictive and prescriptive analytics**. You will guide the team as we build machine-learning models to strengthen forecasting and develop algorithms such as recommendation engines and clustering/segmentation to understand members with similar diagnoses and needs profiles. You don't need to be a research scientist, but you must be technically literate enough in modern ML and data science to set direction, review approaches, partner with our data scientists, and grow analysts into this work.
While setting the strategic vision for the data team, you will actively participate in executing the data strategy, rolling up your sleeves when needed - reviewing designs, unblocking pipelines, and making the hard tradeoff calls. As a people manager, you will foster an environment of mentorship, collaboration, and continuous learning, ensuring your team is empowered to fulfill the broader company vision, including our push to make AI a genuine multiplier for how the team works.
You will work closely with leaders from Product, Accounts, Operations, and the C-suite - as well as external clients and partners to ensure alignment and successful delivery of the data strategy, acting as both a leader and an advocate for the data function across the organization. Because The Helper Bees operates in healthcare, you will do all of this in an environment that requires careful handling of protected health information (PHI).

Requirements Supervisory Responsibilities:
  • Data Engineer(s)
  • Data Analysts/Business Analysts
Duties/Responsibilities:
  • Lead and manage the Data Engineering & Analytics team, providing mentorship, guidance, and support to ensure technical and professional development across a team of mixed tenure, including members still onboarding.
  • Design, implement, and maintain The Helper Bees' data products using Python, SQL, dbt, Airflow, BigQuery, and other modern technologies.
  • Own the team's intake and prioritization - how requests come in, get triaged, and get scheduled (managed in Jira) - and make that process legible to stakeholders so they can see where their requests stand and why.
  • Champion a dbt-first, governed approach: move reporting off manual and bespoke SQL into tested, traceable, automated models, and hold the team to a high reliability bar (on-time delivery and zero manual edits to production data).
  • Lead the team's expansion into predictive and prescriptive analytics - guiding the development of ML models for forecasting, recommendation engines, and clustering/segmentation to profile members by diagnosis and need - and put the practices in place (validation, monitoring, governance) to deploy and maintain these models responsibly in a healthcare context.
  • Set strategic goals for the team, ensuring alignment with the company's data objectives and promoting continuous improvement.
  • Collaborate with department teams to design, build, test, and implement new features and enhancements that meet internal and external stakeholder needs.
  • Monitor team performance and development, fostering an environment of growth through regular feedback, code reviews, and training opportunities.
  • Produce quality, testable, and maintainable code, while setting high coding standards for the team.
  • Assist in refining and improving development processes such as deployment, sprint planning, monitoring, incident response, escalation, and team workflows.
  • Drive adoption of AI tooling (e.g., Cursor, Claude Code) as a multiplier for the team's engineering and analytics work - modeling personal use, and making AI experimentation and sharing a standing team practice.
  • Facilitate problem-solving and innovation within the team, encouraging creative solutions to complex technical challenges.
  • Act as a technical leader for the team, growing other engineers and analysts through mentorship and example, while ensuring high-quality, scalable, and optimized data systems.
  • Quickly isolate and debug complex issues across data pipelines and models, helping the team troubleshoot problems effectively.
  • Collaborate with stakeholders, product teams, operations, external clients, and partners to understand requirements, discuss tradeoffs, and deliver viable solutions.
  • Own the data team's contribution to the monthly close and scorecard - client and partner reports and invoices delivered accurately and on time - and surface exceptions proactively.
  • Drive process improvements within the team, measuring the impact on delivery reliability, efficiency, and overall productivity.
  • Other duties as assigned or necessary to support team and company success.
Performance Metrics:
  • Data Quality: Ensure high standards of data accuracy, completeness, and consistency by setting targets for improving data quality and enforcing data governance standards.
  • Timeliness of Reporting: Lead the team in reducing reporting turnaround times to support timely decision-making and operational efficiency.
  • Technical Leadership: Set clear technical directions and goals for the team. Evaluate your own and your team’s effectiveness in influencing stakeholders, mentoring team members, and adopting strategic initiatives.
  • Code Quality and Maintainability: Monitor and assess the quality of code produced by the team, aiming for high standards of readability, scalability, and maintainability.
  • Problem Solving and Innovation: Track the team’s ability to debug complex issues and foster a culture of innovation by
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