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Manager Data Analytics Engineer Jobs in Grapevine, TX

... value engineering and cost saving initiatives and evaluation of alternates * Data analytics for ... Sets out risk management policy and auditing compliance * Pro-actively leads all commercial risk ...

Lead, mentor, and develop a team of Data Engineers and Analytics Engineers, fostering a culture of engineering excellence and continuous improvement * Establish team goals, manage performance, and ...

They are seeking an Analytics Engineer to join their Global Data Analytics team, where the role involves delivering scalable analytics solutions by translating business needs and collaborating with ...

Analytics Engineer

Garland, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are looking for an Analytics Engineer to join our Global Data Analytics team and help deliver ... No supervisor, manager or executive of the company, other than the General Manager in a signed ...

Analytics Engineer

Garland, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are looking for an Analytics Engineer to join our Global Data Analytics team and help deliver ... No supervisor, manager or executive of the company, other than the General Manager in a signed ...

Director, Data Analytics Engineering

Irving, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Director will lead a team of analytics engineering managers and partner closely with Data Engineering, AI/ML Engineering, Product Management, Architecture, Platform Engineering, and business ...

Showing results 21-40

Manager Data Analytics Engineer information

See Grapevine, TX salary details

$41.1K

$119.8K

$164K

How much do manager data analytics engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for manager data analytics engineer in Grapevine, TX is $119,842.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,800.00 and $127,000.00 per year, depending on experience, location, and employer.

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 popular job titles related to Manager Data Analytics Engineer jobs in Grapevine, TX?

For Manager Data Analytics Engineer jobs in Grapevine, TX, the most frequently searched job titles are:

What job categories do people searching Manager Data Analytics Engineer jobs in Grapevine, TX look for?

The top searched job categories for Manager Data Analytics Engineer jobs in Grapevine, TX are:

What cities near Grapevine, TX are hiring for Manager Data Analytics Engineer jobs?

Cities near Grapevine, TX with the most Manager Data Analytics Engineer job openings:

Senior Manager, Data Analytics and Insights

Fidelity Investments

Westlake, TX

Full-time

Re-posted 8 days ago


Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 271 frontline employees who took The Breakroom Quiz

15th of 150 rated financial services


Job description

Job Description:

Note: Fidelity will not provide immigration sponsorship for this position.

Position Description:

Develops, implements, and deploys analytic solutions to drive actionable intelligence, transformative insights, automation, and effective control in support of business units, clients, and the enterprise. Designs and builds dashboards and reports using Power BI and Tableau to deliver clear and actionable insights. Conducts advanced analytics including trend analysis, segmentation, and predictive modeling using Python to identify growth opportunities and mitigate risks. Extracts and integrates data from multiple environments including SQL databases, Snowflake, and Alteryx workflows to create unified datasets for analysis. Utilizes analytic tools including Alteryx for data preparation, SQL and Snowflake for querying and data integration, Python for statistical modeling, and Power BI and Tableau for dashboard development.

Primary Responsibilities:

  • Defines and leads enterprise-level data strategy and analytics initiatives.

  • Delivers actionable analytics to optimize performance and scale growth.

  • Develops scalable data science solutions for enterprise-level challenges and applies advanced modeling techniques to complex datasets.

  • Supports strategy development, business analysis, risk evaluation, and opportunity assessment.

  • Advises teams on best practices in experimentation and model validation.

  • Advises senior leadership on data-driven decision-making.

  • Delivers ad hoc analyses and strategic insights to support initiatives in client reporting and product performance.

  • Develops strong partnerships with business stakeholders to understand reporting needs and strategic objectives.

  • Implements innovative solutions by leveraging emerging technologies and automation to improve data accessibility and efficiency.

  • Promotes data democratization by developing self-service tools and templates that empower business partners to access and interpret data independently.

  • Mentors junior analysts.

  • Performs independent and complex technical and functional analysis for multiple divisional initiatives.

  • Develops innovative insights to support strategic business goals.

Education and Experience:

Bachelor's degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Senior Manager, Data Analytics and Insights (or closely related occupation) performing advanced data analytics and visualization in a client reporting and business intelligence domain.

Or, alternatively, Master's degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Senior Manager, Data Analytics and Insights (or closely related occupation) performing advanced data analytics and visualization in a client reporting and business intelligence domain.

Skills and Knowledge:

Candidate must also possess:

  • Demonstrated Expertise ("DE") performing data extraction, transformation, cleansing, and data quality checks using SQL, Snowflake, Adobe Analytics, and Alteryx; and automating workflows and Extract, Transform, Load (ETL) processes, as well as integrating datasets with 100,000 + rows of data from multiple sources, using Alteryx.

  • DE translating business requirements into technical specifications using PowerPoint, and creating prototypes for reporting solutions using Figma, Power BI, or Tableau; developing interactive dashboards and visualizations as well as designing client reporting solutions, using Power BI; and advancing stakeholder decisionmaking by applying visualization best practices, using Power BI and Tableau.

  • DE conducting statistical analysis using Python; performing predictive modeling and forecasting using Python; and executing segmentation and trend analysis using Python.

  • DE generating customized reports and client insights using SQL and PowerBI; creating customized dashboards for dynamic business needs using Power BI; and monitoring Key Performance Indicators (KPIs) and enhancing performance metrics, using Power BI.

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Fidelity's Onsite Working Model
Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

Certifications:Category:Business Analytics and Insights

Please be advised that Fidelity's business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.


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