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

H.E.B.

Data Engineering Manager

San Antonio, TX · On-site

$150 - $210/hr

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 ...

Pwc

Data Engineer - Senior Manager

San Antonio, TX

$124K - $280K/yr

In data engineering at PwC, you will focus on designing and building data infrastructure and ... As a Senior Manager you lead large projects, innovate processes, and maintain operational ...

Real Soft, Inc.

Data Scientist

San Antonio, TX · On-site

Citizenship required . * 9+ years of relevant experience in data science, data engineering ... Experience defining and managing data schemas and normalization standards * Strong attention to ...

Deloitte

Senior Manager Data Lead

San Antonio, TX · On-site

Join our AI & Engineering team in transforming technology platforms, driving innovation, and ... We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring ...

Pwc

Data Strategy-Manager

San Antonio, TX

$99K - $232K/yr

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

SWBC

Junior Data Engineer

San Antonio, TX

$103K - $124K/yr

Builds and manages cloudnative data architectures (data warehouse, lakehouse, and streaming) that ... Bachelor's degree or higher in Computer Science, Engineering, Data Science, or related field.

Swbc

Junior Data Engineer

San Antonio, TX

$103K - $124K/yr

Builds and manages cloudnative data architectures (data warehouse, lakehouse, and streaming) that ... Bachelor's degree or higher in Computer Science, Engineering, Data Science, or related field.

SWBC

Junior Data Engineer

San Antonio, TX · On-site

$103K - $124K/yr

Builds and manages cloud-native data architectures (data warehouse, lakehouse, and streaming) that ... Bachelor's degree or higher in Computer Science, Engineering, Data Science, or related field.

Lowe's

Facility Manager - Data Center

San Antonio, TX · On-site

... Engineering Trade license and/or trade school degree in Electrical, Plumbing, Mechanical HVAC, or Controls College degree in facility management, industrial engineering, mechanical engineering ...

Guidehouse

Senior Data Engineer

San Antonio, TX · On-site

$80K - $133K/yr

Develop and maintain data engineering solutions using Python, SQL, Spark, and related technologies ... Ability to independently manage technical tasks and collaborate effectively across teams.

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Showing results 1-20

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

Manager Data Engineering information

See Seguin, TX salary details

$27.6K

$86.4K

$152.9K

How much do manager data engineering jobs pay per year?

As of Sep 5, 2026, the average yearly pay for manager data engineering in Seguin, TX is $86,357.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,700.00 and $111,600.00 per year, depending on experience, location, and employer.

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.

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.

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 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 cities near Seguin, TX are hiring for Manager Data Engineering jobs?

Cities near Seguin, TX with the most Manager Data Engineering job openings:

Manager Data Engineering jobs near you
Infographic showing various Manager Data Engineering job openings in Seguin, TX as of August 2026, with employment types broken down into 84% Full Time, 15% Part Time, and 1% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $86,357 per year, or $41.5 per hour.

Data Engineering Manager

H.E.B.

San Antonio, TX • On-site

$150 - $210/hr

Other

Re-posted 13 days ago

Job description

Responsibilities

We are seeking an experienced Data Engineering Manager to lead the design, development, and delivery of scalable data platforms and data products that power personalized customer experiences across digital retail channels. 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 solutions that enable personalized product search, search ranking, recommendations, customer segmentation, behavioral analytics, and omnichannel personalization.

As a people leader, you will be responsible for hiring, onboarding, coaching, performance management, succession planning, and career development while fostering a culture of innovation, operational excellence, and continuous improvement. You will partner closely with Product Management, Data Science, Machine Learning Engineering, Search Engineering, Customer Experience, and senior technology leaders to deliver strategic initiatives that drive measurable business outcomes.

The ideal candidate combines deep expertise in modern data engineering and large-scale data platforms with proven leadership experience and a strong understanding of customer behavior data, personalization systems, recommendation engines, and cloud-based technologies.

Key Responsibilities & Essential FunctionsLeadership & Team Management
  • Lead, mentor, and develop a high-performing team of Data Engineers across one or more engineering squads.
  • Foster an environment of accountability, collaboration, innovation, and customer-centric thinking.
  • Manage all people leadership responsibilities, including hiring, onboarding, performance reviews, career development, promotions, succession planning, compensation planning, and employee engagement.
  • Coach and mentor engineers in engineering best practices, technologies, processes, and career growth.
  • Empower team members to be autonomous, highly effective, and capable of delivering scalable solutions.
  • Establish engineering standards, coding practices, operational excellence frameworks, and delivery processes.
  • Drive Agile planning, sprint execution, prioritization, and delivery of strategic initiatives.
Data Platform & Engineering
  • Lead the design, development, and operation of scalable batch, streaming, and real-time data platforms.
  • Develop and maintain data products supporting:
    • Personalized product search
    • Search relevance and ranking optimization
    • Product recommendations
    • Customer segmentation
    • Customer identity and householding
    • Behavioral analytics
    • Omnichannel personalization
  • Design scalable data architectures utilizing modern lakehouse, data lake, and cloud-native patterns.
  • Build and support feature stores, APIs, and data services used by machine learning and personalization systems.
  • Ensure high levels of data quality, reliability, observability, governance, security, and compliance.
  • Optimize platform performance, scalability, availability, and cost efficiency.
  • Implement monitoring, alerting, SLA management, and incident response procedures for production data platforms.
Technical Strategy & Architecture
  • Develop technical roadmaps aligned with business priorities and long-term organizational objectives.
  • Lead the technical design and delivery of complex initiatives across multiple systems and platforms.
  • Recommend improvements to architecture, scalability, reliability, security, performance, and operational processes.
  • Evaluate emerging technologies and industry best practices to enhance platform capabilities.
  • Guide engineering teams on architectural decisions, code quality, design reviews, and technical standards.
  • Assist in diagnosing and resolving highly complex technical and operational issues.
Customer Personalization & Machine Learning Enablement
  • Build foundational data capabilities that support:
    • Product recommendation engines
    • Customer 360 platforms
    • Customer identity resolution
    • Clickstream analytics
    • Purchase behavior analysis
    • Real-time personalization
    • Search relevance optimization
    • Behavioral event processing
  • Partner with Data Scientists and Machine Learning Engineers to operationalize and scale personalization models.
  • Enable experimentation, A/B testing, feature engineering, and measurement frameworks that improve customer experiences.
Cross-Functional Collaboration
  • Collaborate closely with Product Management, Data Science, Machine Learning Engineering, Search Engineering, Customer Experience teams, and business stakeholders.
  • Translate business objectives into scalable technical solutions and execution plans.
  • Communicate technical strategy, progress, risks, recommendations, and outcomes to leaders and stakeholders.
  • Lead cross-functional initiatives with significant business impact and organizational visibility.
Operational Excellence
  • Establish operational objectives, work plans, staffing strategies, and resource allocations.
  • Ensure adherence to budgets, timelines, and performance requirements.
  • Implement strategic policies, processes, and standards that support departmental and organizational objectives.
  • Drive continuous improvement through modern engineering practices, automation, observability, and operational excellence.
Qualifications & Key RequirementsWork Experience
  • 8+ years of experience in software engineering, data engineering, or related technical disciplines.
  • 3+ years of experience leading and developing engineering teams.
  • Proven experience delivering large-scale data platform, analytics, or machine learning infrastructure initiatives.
  • Experience managing technical roadmaps, cross-functional projects, and engineering delivery.
Knowledge, Skills & Abilities
  • Strong leadership skills with demonstrated success building and managing high-performing engineering teams.
  • Expert knowledge of data architecture, distributed systems, software design patterns, and engineering best practices.
  • Deep understanding of data modeling, ETL/ELT, streaming architectures, and event-driven systems.
  • Strong expertise with:
    • Python
    • SQL
    • Apache Spark
    • Kafka
    • Data orchestration frameworks
  • Experience with cloud platforms such as AWS and/or Google Cloud Platform.
  • Experience with modern data lake and lakehouse architectures.
  • Experience building APIs, data products, and services supporting machine learning applications.
  • Strong understanding of scalability, reliability, security, observability, and performance engineering.
  • Ability to lead technical strategy while balancing business priorities and organizational goals.
  • Strong communication and stakeholder management skills.
Preferred Qualifications
  • Experience in retail, e-commerce, digital commerce, or customer-facing digital products.
  • Experience supporting:
    • Personalized product search
    • Search ranking and relevance systems
    • Recommendation engines
    • Customer personalization platforms
    • Customer 360 initiatives
  • Experience working with clickstream, behavioral, transactional, and customer identity data.
  • Familiarity with:
    • Recommendation systems
    • Collaborative filtering
    • Embeddings and feature engineering
    • Vector search and semantic search technologies
    • MLOps platforms
    • Feature stores
    • Experimentation frameworks and A/B testing
  • Experience supporting machine learning platforms and production AI/ML workloads.
Education
  • Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related field, or equivalent combination of education and professional experience.
Physical Demands & Working Conditions
  • Ability to function in a fast-paced, multi-priority environment.
  • Ability to travel as needed.
  • May require occasional extended hours to support critical business initiatives and production events.

Last revised: 11/01/2024

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