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

Senior Data Engineer

Houston, TX · On-site

$101K - $137K/yr

Required Experience: * 12+ Years of Data Engineering * Snowflake Data Architecture & Performance ... SQL & Python * Data Governance & Metadata Management * Data Catalog, Lineage & Data Quality

Stakeholder management & executive communication Required Skills & Experience Technical Expertise * 12-17 years of experience in data engineering, data architecture, or analytics platforms. * Deep ...

... management, and data quality are consistently tracked across solutions Partner with Enterprise Data Engineering & Analytics teams to build and support analytics deliverables for production use ...

Represents the data engineering team for all phases of larger and more-complex development projects ... Builds and manages relationships throughout the organization. Provides guidance and mentoring to ...

Data Engineer

Houston, TX

$109K - $131K/yr

... data engineering practice) to deliver analytics-ready data. * Consolidate data from multiple sources into a centralized integration point (e.g., a single SQL Server instance) and manage field ...

Azure Data Engineer

Houston, TX · On-site

$109K - $131K/yr

... data engineering * Advance English level * Expert proficiency in at least one of these programming languages: Python, NoSQL, SQL, R, and competent in source code management * Build processes ...

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 ...

Data Engineer

The Woodlands, TX · On-site

$70 - $85/hr

Utilize Azure services such as SQL Server, Synapse Analytics, Databricks, and Delta Lake to build and manage scalable data infrastructure. and data pipelines * Enable CI/CD & DevOps: Integrate data ...

Sr. Data Engineer

Sugar Land, TX · On-site

$105K - $126K/yr

Sugarland TX - 4 days/week onsite Duration: 12 months Design, develop, and support data engineering ... Partner with business users and the Business Relationship Management team on requirements gathering ...

Manager, Data Analytics We're looking for someone who can sit between the business and the ... partnering with engineering to make it happen Minimum Requirement Degree or equivalent and ...

Data Engineer

Spring, TX · On-site

$70 - $85/hr

Utilize Azure services such as SQL Server, Synapse Analytics, Databricks, and Delta Lake to build and manage scalable data infrastructure. and data pipelines * Enable CI/CD & DevOps: Integrate data ...

Showing results 41-60

Manager Data Engineering information

See Houston, TX salary details

$29.6K

$92.8K

$164.3K

How much do manager data engineering jobs pay per year?

As of Aug 2, 2026, the average yearly pay for manager data engineering in Houston, TX is $92,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,000.00 and $119,800.00 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, and why are they important?

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 Manager Data Engineering roles and responsibilities?

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 of 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 Houston, TX? The most popular types of Data Engineering jobs in Houston, TX are:
What are popular job titles related to Manager Data Engineering jobs in Houston, TX? For Manager Data Engineering jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Manager Data Engineering jobs in Houston, TX look for? The top searched job categories for Manager Data Engineering jobs in Houston, TX are:
What cities near Houston, TX are hiring for Manager Data Engineering jobs? Cities near Houston, TX with the most Manager Data Engineering job openings:
Infographic showing various Manager Data Engineering job openings in Houston, TX as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $92,771 per year, or $44.6 per hour.

IT Data Analytics Director

Apache Corporation

Houston, TX • On-site

Full-time

Re-posted 3 days ago


Job description

Job Title: IT Data Analytics Director
Req Id: 12804
Specific Responsibilities
The Director of AI, Data Analytics, Data Engineering, Data Management, and Application Development, located in Houston, TX, is a senior leadership role responsible for overseeing and integrating multiple data-centric functions within the organization. This role ensures the strategic alignment of AI and data initiatives with business objectives, driving innovation, efficiency, and data-driven decision-making across the enterprise.
This role will be primarily responsible to:
  • Develop and execute the enterprise data, analytics, and AI strategy aligned with business objectives, digital transformation priorities, and long-term business value creation.
  • Lead, mentor, and develop multidisciplinary teams spanning data engineering, analytics, data management, AI/ML, digital products, and application delivery.
  • Foster a culture of innovation, collaboration, operational excellence, accountability, and continuous learning across the organization.
  • Partner with business and technology leaders to identify, prioritize, and deliver high-value data and AI initiatives that improve business performance and operational efficiency.
  • Establish and oversee enterprise analytics capabilities that provide actionable insights to support operational, commercial, and strategic decision-making.
  • Define and govern the enterprise data architecture, including cloud data platforms, data integration patterns, and scalable data products.
  • Oversee the design, implementation, and operation of secure, reliable, and scalable data pipelines, data services, and integration capabilities.
  • Develop and maintain policies, standards, and controls that protect the confidentiality, security, integrity, and availability of enterprise information assets.
  • Lead the identification, development, deployment, and governance of artificial intelligence and machine learning solutions that improve operational performance and business outcomes.
  • Establish responsible AI practices including AI governance, model lifecycle management, model risk management, transparency, explainability, and ongoing monitoring.
  • Drive adoption of generative AI capabilities and AI-assisted software development practices to improve productivity and accelerate solution delivery.
  • Evaluate emerging technologies, industry trends, and market developments to identify opportunities for innovation and competitive advantage.
  • Oversee the delivery, support, and lifecycle management of data-driven applications, low-code solutions, digital products, and workflow automation solutions that support business operations.
  • Ensure applications and digital solutions are scalable, secure, maintainable, user-friendly, and aligned with enterprise architecture standards.
  • Develop and manage annual operating plans, budgets, forecasts, and investment strategies within approved financial targets and organizational variance expectations.
  • Monitor technology spending, cloud and AI consumption, software licensing, and operational costs and implement cost optimization and FinOps practices across the portfolio.
  • Manage strategic relationships with technology vendors, service providers, system integrators, and implementation partners.
  • Lead technology evaluations, proof of concepts, contract negotiations, and vendor performance management activities.
  • Ensure alignment between enterprise IT, cloud, cybersecurity, operational technology (OT), and business organizations to support integrated digital capabilities across the enterprise.

Qualifications & Experience
The successful candidate will have the following qualifications and experience:
  • Bachelor's degree in computer science, data science, information technology, or a related field and/or a minimum of 10 years of experience in data analytics, data engineering, data management, data science, or application development.
  • 10 Years of experience in data analytics, data engineering, data management, data science, or application development.
  • At least 3 years of management experience.
  • Excellent leadership, people management, coaching, and team development capabilities.
  • Strong communication, presentation, negotiation, and stakeholder management skills, including interaction with executive leadership.
  • Strategic thinking with the ability to align technology investments and initiatives with business objectives and measurable business outcomes.
  • Strong analytical, critical thinking, and problem-solving capabilities.
  • Strong program, portfolio, project, and financial management skills.
  • Ability to collaborate effectively across business functions, technical organizations, and external partners.
  • Strong attention to detail and commitment to data quality, governance, and operational excellence.
  • Expertise in modern enterprise data architecture, data engineering, and cloud-native data platforms.
  • Experience designing, implementing, and managing scalable data pipelines, data platforms, and enterprise integration architectures.
  • Proficiency with business intelligence, reporting, and analytics platforms such as Power BI, Sigma, or similar technologies.
  • Experience with modern data platforms and technologies such as Snowflake, Databricks, or equivalent cloud-native solutions.
  • Experience with cloud computing platforms including AWS and Azure.
  • Strong understanding of enterprise data governance, metadata management, master data management, data quality, and information lifecycle management principles.
  • Knowledge of cybersecurity, data privacy, regulatory compliance, and information protection requirements applicable to enterprise data environments.
  • Experience implementing and governing artificial intelligence, machine learning, and generative AI solutions within enterprise environments including ChatGPT, Claude, and Copilot.
  • Knowledge of AI governance, model lifecycle management, model risk management, and responsible AI frameworks.
  • Familiarity with AI-assisted software development practices and modern software engineering methodologies.
  • Understanding of DevSecOps, DataOps, MLOps, CI/CD, and cloud operations practices.
  • Experience supporting low-code and workflow automation platforms.
  • Understanding of relational and analytical database technologies such as Oracle, Microsoft SQL Server, and cloud-native analytical databases.
  • Knowledge of cloud cost management, FinOps practices, and technology portfolio optimization.
  • Experience managing technology vendors, software suppliers, system integrators, and strategic technology partnerships.
  • Ability to evaluate emerging technologies and determine business applicability and value.
  • Understanding of operational technology (OT), industrial data management, and enterprise integration challenges in complex industrial environments.
  • Experience in upstream environments is preferred.
  • Demonstrated ability to balance innovation, operational reliability, cybersecurity, and regulatory compliance in large enterprise environments.

Competencies
The successful candidate will lead by example through successfully demonstrating the following:
  • Core Competencies
    • Communication: Writes, speaks, and presents information effectively and persuasively across communication setting;
    • Results: Pursues work with energy, drive, and results orientation to positively impact Apache's business success;
    • Collaboration: Works in partnership with others and encourages different perspectives, while building and maintaining trust; and
    • Culture: Willingness and ability to align one's behavior with the needs, priorities, and goals of Apache.
  • Leadership Competencies
    • Servant Leadership: Inspires and enables performance excellence through feedback, empathy, development and empowerment;
    • Strategic Mindset: Applies business acumen to see the big picture, understand business issues, and exhibit financial stewardship;
    • Change Leadership: Inspires change by challenging the status quo, generating support, and executing improvement projects to achieve business outcomes; and
    • Leading Effective Teams: Enables performance excellence through effective structure, delegation, and motivation.

Company Overview
Our primary product is energy, and where there is affordable, abundant energy, people are healthier, have access to better education, and are given greater opportunities to elevate their families to higher standards of living.
Nearly 3 billion people - roughly one-third of the global population - live without electricity or without clean cooking facilities. We are committed to providing energy in innovative and more sustainable ways to help raise the standard of living for those living in energy poverty and to meet the ongoing demands of people and economies around the world.
The products we deliver power increasingly cleaner electricity across the globe, fuel tractors and trucks, make fertilizer to keep the world's food supply on the table, and heat our schools, hospitals and businesses.
Our employees bring a wide range of talents and skills to the job every day to tackle complex business challenges. We believe in providing a truly rewarding work environment supported by a benefits platform that ranks among the best in our peer group. Our company offers career development opportunities where employees can grow personally and professionally. We promote employee benefits that cultivate a family-friendly work environment and focus on our employees' overall well-being.
We are committed to being a workplace where all employees are valued and can thrive with a sense of belonging. Our commitment to non-discriminatory, equal employment opportunities benefits our individual employees, our company and our external stakeholders; we are better as an organization when various experiences, ideas, and perspectives are brought to the table.
Apache Corporation is a wholly owned subsidiary of APA Corporation (NASDAQ:APA). Apache has operations in the United States, Egypt's Western Desert and the United Kingdom's North Sea and a sister company with exploration opportunities offshore Suriname. Whether supporting Apache, APA Corporation or one of its subsidiaries, team members are employed by Apache Corporation.
For additional information about APA Corporation, please visit:
Portfolio
Sustainability
Investors
www.apacorp.com
Apache Statement on Hiring
To provide genuine equal opportunity to all people, it is the policy of Apache Corporation and its subsidiaries to base all employment-related decisions and actions exclusively on employment-related criteria. To provide genuine equal opportunity to all people, it is the policy of Apache Corporation and its subsidiaries to provide broad dissemination of job opportunities, as consistent with the nature of the positions. To provide genuine equal opportunity to all people, it is the policy of Apache Corporation and its subsidiaries to review its employment-related policies and actions on a regular basis to ensure that their application is consistent with their intent.
Equal Employment Opportunity