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Manager Data Engineering Jobs in Prosper, TX (NOW HIRING)

GM Financial

Manager - Data Engineering

Irving, TX · On-site

$106K - $127K/yr

Work with data engineering related groups to inform on and showcase capabilities of emerging ... Strong working knowledge of disaster recovery, incident management, and security best practices

ABC Financial

Senior Manager, Data Engineering

Frisco, TX · On-site +1

$198K - $208K/yr

Senior Manager, Data Engineering Position Location: 2600 North Dallas Parkway, Suite 590, Frisco, TX 75034 Salary: $198,409.52 - $208,780.00 per year Hours: Monday - Friday, 8:00 am to 5:00 pm ...

7-ELEVEN

Senior Manager, Data Engineering

Irving, TX · On-site

We are looking for an experienced Engineering Manager to lead the Data Engineering team. At 7-Eleven, Enterprise Data powers decisions for everyone from store managers to the C-suite. The Data ...

HEB

Data Engineering Manager

Dallas, TX · On-site

This leader will manage and develop a team of Data Engineers responsible for building reliable, secure, and high-performance data pipelines, machine learning data infrastructure, and customer data ...

Owens & Minor

Senior Manager, Data Engineering

Dallas, TX · On-site +1

$140K - $155K/yr

Key Responsibilities Leadership & Team Management - Lead, mentor, and develop a team of data engineers and BI developers -Establishdelivery standards, performance expectations, and career development ...

Core Specialty

Director, Data Engineering

Dallas, TX · On-site

The remaining 40% will be focused on strategic alignment, technical direction, and resource management for the Data Engineering team. A key part of the mandate is ensuring the platform remains AI/ML ...

New

1 point system

Data Engineering Manager

Dallas, TX · On-site

$113K - $136K/yr

Qualifications * 6+ years of experience in data engineering and delivery leadership. * Proven track record managing delivery of Snowflake-based data platforms (pipelines, ETL, semantic layers). Hands ...

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All JobsData Engineering JobsManager Data Engineering JobsManager Data Engineering Jobs in Prosper, TX

Manager Data Engineering information

See Prosper, TX salary details

$28.4K

$89K

$157.5K

How much do manager data engineering jobs pay per year?

As of Aug 9, 2026, the average yearly pay for manager data engineering in Prosper, TX is $88,964.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,400.00 and $114,900.00 per year, depending on experience, location, and employer.

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

AspectManager Data EngineeringData Engineer
Required CredentialsBachelor's or Master's in CS, Data Science, or related; often leadership experienceBachelor's or higher in CS, IT, or related; technical certifications optional
Work EnvironmentTeam leadership, project management, strategic planningData pipeline development, coding, data modeling
Employer & Industry UsageTech companies, finance, healthcare, where data teams are commonData-focused roles across various industries

The main difference is that Manager Data Engineering oversees data teams and projects, focusing on strategy and leadership, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Managers typically have more experience and leadership skills, whereas Data Engineers are more hands-on with coding and data architecture.

What are the key skills and qualifications needed to thrive as a manager data engineering?

To thrive as a Manager Data Engineering, you need expertise in data architecture, advanced analytics, and leadership, typically supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), data warehousing systems, cloud platforms (AWS, Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong communication, problem-solving, and team management skills help drive project success and foster collaboration. These skills ensure effective data solutions, alignment with business goals, and the ability to lead and grow high-performing engineering teams.

What are the roles and responsibilities of a manager data engineering?

A Manager Data Engineering oversees teams that design, build, and maintain data infrastructure and pipelines for organizations. They are responsible for ensuring the efficient flow and storage of data, implementing best practices in data management, and collaborating with stakeholders to meet business data needs. Additionally, they mentor and guide data engineers, manage project timelines, and ensure data security and quality standards are met. Their role often involves strategic planning to enable data-driven decision making across the company.

How does a manager data engineering typically collaborate with data scientists and business stakeholders?

A Manager of Data Engineering often serves as a bridge between technical teams and business stakeholders. They work closely with data scientists to ensure that data pipelines and infrastructure meet analytical needs, while also translating business requirements into actionable engineering solutions. Regular coordination meetings, clear documentation, and cross-functional projects are common, enabling seamless collaboration and alignment on goals. This role requires strong communication skills and the ability to balance technical priorities with business objectives.
What are the most commonly searched types of Data Engineering jobs in Prosper, TX? The most popular types of Data Engineering jobs in Prosper, TX are:
What are popular job titles related to Manager Data Engineering jobs in Prosper, TX? For Manager Data Engineering jobs in Prosper, TX, the most frequently searched job titles are:
What job categories do people searching Manager Data Engineering jobs in Prosper, TX look for? The top searched job categories for Manager Data Engineering jobs in Prosper, TX are:
What cities near Prosper, TX are hiring for Manager Data Engineering jobs? Cities near Prosper, TX with the most Manager Data Engineering job openings:
Manager Data Engineering jobs near you
Infographic showing various Manager Data Engineering job openings in Prosper, TX as of July 2026, with employment types broken down into 84% Full Time, 14% Part Time, 1% Temporary, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $88,964 per year, or $42.8 per hour.

Manager - Data Engineering

GM Financial

Irving, TX • On-site

$106K - $127K/yr

Full-time

Retirement

Posted 6 days ago

GM Financial rating

7.9

Company rating: 7.9 out of 10

Based on 41 frontline employees who took The Breakroom Quiz

76th of 171 rated vehicle equipment hire

Job description


Why GM Financial Technology
Innovation isn't just a talking point at GM Financial, it's how we operate. From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech teams are building real solutions that make a difference. We're committed to AI-powered transformation, using advanced machine learning and automation to help us reimagine customer interactions and modernize operations, positioning GM Financial as a leader in digital innovation within a dynamic industry.
Join us and discover a workplace where your ideas matter, your development is prioritized, and you can truly make a global impact.
Work Arrangement: Hybrid - 2 days onsite, 3 days remote per week
Responsibilities
About the role:
We are expanding our efforts into complementary data technologies for analytics and decision support in areas of ingesting and processing large data sets. Our interests are in enabling data science and search based applications on large and low latent data sets in both a batch and streaming context for processing. To that end, this role will engage with team counterparts in exploring, developing and deploying technologies for creating data sets using a combination of batch and streaming transformation processes. These data sets support both off-line and in-line machine learning training and model execution. Other data sets support search engine based analytics. Exploration and deployment of technologies activities include identifying opportunities that impact business strategy, selecting data solutions software, and defining hardware requirements based on business requirements. Responsibility also includes coding, testing, and documentation of new or modified scalable analytic data systems including automation for deployment and monitoring. This role participates along with team counterparts to architect an end-to-end framework developed on a group of core data technologies. Other aspects of the role include developing standards and processes for data engineering projects and initiatives.
What makes you a dream candidate?
  • Evaluate, research, experiment with data engineering technologies in a lab to keep pace with industry innovation while assessing business impact and viability for use cases associated with efforts in hand
  • Work with data engineering related groups to inform on and showcase capabilities of emerging technologies and to enable the adoption of these new technologies and associated techniques
  • Define and refine processes and procedures for the data engineering practice
  • Work closely with data scientists, data architects, ETL developers, other IT counterparts, and business partners to identify, capture, collect, and format data from the external sources, internal systems, and the data warehouse to extract features of interest
  • Code, test, deploy, monitor, document, and troubleshoot data engineering processing and associated automation
  • Define data engineering architecture both hardware and software reflective of business requirements to be included in end-to-end solution architecture
  • Educate and develop ETL developers on data engineering so as to enable transition to data engineer and practice
  • Conduct code reviews, suggest improvements, support technology upgrades for the common libraries, handover them to the corresponding development teams for quality check and support them till deployment into production
  • Support ETL developers and Operations teams to troubleshooting of the incidents for root cause analysis and assist in solutioning to meet the service level agreements
  • Work with Operations teams in Big Data, IT and Information Security with monitoring and troubleshooting of incidents to maintain service levels
  • Contribute to the evolving distributed systems architecture to meet changing requirements for scaling, reliability, performance, manageability, and cost
  • Report utilization and performance metrics to user communities
  • Contributes to planning and implementation of new/upgraded hardware and software releases
  • Responsible for monitoring the Linux, Hadoop, and Spark communities and vendors and report on important defects, feature changes, and or enhancements to the team
  • Research and recommend innovative, and where possible, automated approaches for administration tasks
  • Identify approaches to efficiencies in resource utilization, provide economies of scale, and simplify support issues

Qualifications
Have Other Skills? We Use These Too
  • Strong working knowledge of Hadoop and Spark cluster security, networking connectivity and IO throughput along with other factors that affect distributed system performance
  • Strong working knowledge of disaster recovery, incident management, and security best practices
  • Working knowledge of containers (e.g., docker) and major orchestrators (e.g., Mesos, Kubernetes, Docker Datacenter)
  • Working knowledge of automation tools (e.g., Puppet, Chef, Ansible)
  • Working knowledge of software defined networking
  • Working knowledge of parcel based upgrades with Hadoop (i.e., Cloudera)
  • Working knowledge of hardening Hadoop with Kerberos, TLS, and HDFS encryption
  • Working knowledge with directed analytic graph stream processing using Beam, Flink, Nifi and/or Samza
  • Excellent knowledge of Linux, AIX, or other Unix flavors
  • Working knowledge of Cloud based implementations (e.g., Microsoft Azure) with emphasis on security using ACLs and Artifactory Groups
  • Ability to accept change and to adapt to shifting organizational challenges and priorities
  • Ability to coach, develop and lead others
  • Ability to evaluate problems and issues quickly, and to make recommendations for courses of action
  • Ability to make independent decisions and use sound judgment in relation to the management of team members
  • Ability to prioritize tasks and ensure their completion in a timely manner
  • Excellent analytical and troubleshooting skills
  • Strong interpersonal, verbal and written skills

Work Experience
  • 5-7 years experience with software engineering to include Java, Scala, and Python required
  • 5-7 years proficiency with processing large data sets with Kafka, RabbitMQ, Flume, Hadoop, HBase, Cassandra and/or Spark or similar distributed system required
  • 3-5 years hands-on experience with scripting with Bash, Perl, Ruby required
  • 3-5 years hands-on development / processing experience on Kafka, HBase, Solr, and Hue required
  • 2-4 years hands-on experience with ETL and Business Intelligence technologies such as Informatica, DataStage, Ab Initio, Cognos, BusinessObjects, or Oracle Business Intelligence required
  • 2-3 years hands-on experience with SQL, data modeling, and relational databases such as Oracle, DB2, and Postgres required
  • Proven track record with NoSQL data stores such as MongoDB, Cassandra, HBase, Redis, Riak or other technologies that embed NoSQL with search such as MarkLogic or Lily Enterprise required
  • 0-2 years management experience with data engineering team preferred
  • High School Diploma or equivalent required
  • Bachelor's Degree in related field or equivalent work or military experience required

Additional Knowledge and Skills
Working effectively within an AI enabled environment:
  • Ability to use AI tools (e.g., Microsoft Copilot) to support daily work
  • Skills in evaluating AI outputs for accuracy, compliance, and bias
  • Experience integrating AI into workflows to improve efficiency or insights
  • Familiarity with AI assisted research, summarization, and content generation
  • Understanding of responsible AI use, including ethics and data protection
  • Experience with AI assisted software development or automation
  • Knowledge of prompting techniques to improve output quality
  • Awareness of emerging GenAI capabilities and limitations

What We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays.
Our Culture: Our team members define and shape our culture - an environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work - we thrive.
Compensation: Competitive pay and bonus eligibility.
Work Life Balance: Flexible hybrid work environment, 2-days a week in office.
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