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Technology Operations Enterprise Data Strategy Jobs in Houston, TX

Kanshe Infotech

Enterprise Data Architect

Houston, TX · On-site

Support enterprise data strategy, MDM, governance, and architecture standards. * Participate in Architecture Review Boards (ARBs) and technical design reviews. * Evaluate SaaS/ERP applications and ...

Kanshe Infotech

Enterprise Data Architect

Houston, TX · On-site

$70 - $75/hr

Support enterprise data strategy, MDM, governance, and architecture standards. * Participate in Architecture Review Boards (ARBs) and technical design reviews. * Evaluate SaaS/ERP applications and ...

IS3 Solutions

Senior Enterprise Data Architect

Houston, TX · On-site

$64.25 - $86/hr

Responsibilities : • Define and maintain the enterprise data architecture strategy including data ... technology adoption • Support the customer's Emergency Operation Plan by ensuring data ...

Hp

Principal Data Architect

Spring, TX

Lead enterprise data strategy , aligning data initiatives with business, AI, and digital ... Drive adoption of new technologies (GenAI, agentic systems, streaming architectures, data mesh)

Goodwill of Houston

VP of IT

TX · On-site

$149K - $187K/yr

Serves as a strategic and operational leader responsible for advancing Goodwill Houston ... Data & Analytics Lead enterprise data strategy, including governance, quality, and accessibility.

Oxy

Advisor - Data Trust & AI Products

Houston, TX · On-site

This role offers a rare opportunity to influence enterprise data strategy, build cutting-edge AI ... Evaluate emerging AI technologies and drive innovation across the enterprise. * Translate business ...

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All JobsTechnology Operations Enterprise Data Strategy JobsTechnology Operations Enterprise Data Strategy Jobs in Houston, TX

Technology Operations Enterprise Data Strategy information

See Houston, TX salary details

$24

$68

$87

How much do technology operations enterprise data strategy jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for technology operations enterprise data strategy in Houston, TX is $68.68, according to ZipRecruiter salary data. Most workers in this role earn between $59.66 and $78.75 per hour, depending on experience, location, and employer.

What is Technology Operations Enterprise Data Strategy?

Technology Operations Enterprise Data Strategy refers to the planning, management, and implementation of data-related processes and technologies across an organization to support its operational goals. This role involves setting standards for data governance, ensuring data quality, and aligning data initiatives with business objectives. Professionals in this field work to optimize data flow, storage, and security, enabling better decision-making and efficiency. They often collaborate with IT, business units, and data analytics teams to ensure data assets are leveraged effectively across the enterprise.

How does a Technology Operations Enterprise Data Strategy professional typically collaborate with other departments within an organization?

Professionals in Technology Operations Enterprise Data Strategy work closely with multiple departments, such as IT, business analytics, compliance, and executive leadership. They often facilitate communication between technical teams and business stakeholders to ensure that data initiatives align with organizational goals. This role involves coordinating data governance policies, integrating new technologies, and supporting data-driven decision-making across the enterprise. Successful collaboration requires strong communication skills and a deep understanding of both technical and business perspectives.

What are the key skills and qualifications needed to thrive in Technology Operations Enterprise Data Strategy, and why are they important?

To excel in Technology Operations Enterprise Data Strategy, you need strong expertise in data management, analytics, and strategic planning, often backed by a degree in computer science, information systems, or a related field. Familiarity with data warehousing solutions, ETL tools, data governance frameworks, and certifications like CDMP or AWS Certified Data Analytics is highly valuable. Exceptional problem-solving, stakeholder management, and communication skills help drive cross-functional initiatives and align data strategies with business goals. These competencies ensure effective data-driven decision making, operational efficiency, and long-term organizational success.

What is the difference between Technology Operations Enterprise Data Strategy vs Data Analyst?

AspectTechnology Operations Enterprise Data StrategyData Analyst
CredentialsTypically requires a degree in IT, Data Science, or related fields; certifications like CDMP or CBIP are commonRequires a degree in Statistics, Data Science, or related fields; certifications like Microsoft Data Analyst Associate or Tableau Desktop Specialist are common
Work EnvironmentFocuses on strategic planning, data governance, and infrastructure within enterprise IT teamsFocuses on data collection, analysis, and reporting to support business decisions
Employer & Industry UsageUsed in large organizations managing enterprise data assets and IT operationsUsed across industries for data reporting, visualization, and insights

While Technology Operations Enterprise Data Strategy professionals focus on aligning data initiatives with business goals and managing data infrastructure, Data Analysts primarily analyze data to generate actionable insights. Both roles require strong analytical skills but differ in scope and strategic involvement.

What cities near Houston, TX are hiring for Technology Operations Enterprise Data Strategy jobs?

Cities near Houston, TX with the most Technology Operations Enterprise Data Strategy job openings:

Technology Operations Enterprise Data Strategy jobs near you

Enterprise Data Architect Consultant

CG Infinity

Houston, TX • On-site

$120 - $190/hr

Other

Posted 29 days ago

Job description

Enterprise Data Architect Consultant Position Summary

CG Infinity is seeking a strategic and hands‑on Enterprise Data Architect to design, build, and lead the implementation of a scalable, enterprise‑wide data Lakehouse. This role will be responsible for developing a modern data architecture from the ground up, integrating multiple systems and business units into a unified data ecosystem that drives analytics, reporting, and business decision‑making.

The ideal candidate combines deep technical expertise with strong business acumen, capable of leading discovery efforts, defining priorities, and ensuring data solutions are aligned with organizational goals. This individual will also play a key leadership role in establishing data governance, master data management (MDM), and enterprise data standards.

Key Responsibilities Enterprise Data Architecture & Strategy
  • Design and implement a scalable, secure, and high‑performance enterprise data Lakehouse from inception.
  • Define the end‑to‑end data architecture, including data ingestion, transformation, storage, integration, and consumption layers.
  • Establish architectural standards, frameworks, and best practices aligned with business and technology strategies.
  • Evaluate and recommend technologies (cloud platforms, ETL/ELT tools, data lakes, Lakehouses) to support long‑term scalability.
Cross‑Functional Discovery & Requirements Alignment
  • Lead discovery sessions with business and technical stakeholders to identify high‑value use cases, priorities, and dependencies.
  • Translate business requirements into technical data models, data flows, and architecture designs.
  • Ensure alignment between data solutions and business objectives, including KPIs, reporting, and analytics needs.
  • Develop and maintain a data roadmap with clearly defined phases, milestones, and deliverables.
Data Lakehouse Development & Delivery
  • Oversee development of integrated data pipelines that connect disparate systems (ERP, CRM, operational systems, third‑party platforms).
  • Define and implement data models (conceptual, logical, physical) to support analytics and reporting.
  • Establish data quality frameworks and ensure reliability, consistency, and integrity of enterprise data.
  • Ensure performance optimization and scalability of the data environment.
Data Governance & Master Data Management
  • Develop and implement enterprise data governance policies, standards, and controls.
  • Lead Master Data Management (MDM) initiatives to standardize key business entities across systems.
  • Define data ownership, stewardship, and accountability models across business units.
  • Ensure compliance with regulatory, security, and data privacy requirements.
Leadership & Stakeholder Engagement
  • Act as a trusted advisor to executive leadership, including the CTO and business leaders.
  • Communicate complex technical concepts clearly to non‑technical stakeholders.
  • Lead cross‑functional teams, including data engineers, analysts, and business users.
  • Drive adoption of data solutions across the organization through change management and stakeholder alignment.
Required Qualifications
  • 8+ years of experience in data architecture, data engineering, or enterprise data management roles.
  • Proven experience building an enterprise data Lakehouse from scratch spanning multiple systems and business units.
  • Strong experience with data modeling, ETL/ELT design, and data integration frameworks.
  • Hands‑on experience with cloud data platforms (e.g., Azure, AWS, or GCP).
  • Demonstrated expertise in:
    • Python Development
    • Data Governance frameworks
    • Master Data Management (MDM)
    • Data quality and metadata management
  • Experience leading discovery sessions and requirements gathering workshops with senior stakeholders.
  • Strong understanding of enterprise systems (ERP, CRM, operational apps) and integration patterns.
  • Excellent communication, facilitation, and leadership skills.
Preferred Qualifications
  • Experience in consulting environments or multi‑client, multi‑business unit organizations.
  • Industry experience in oil & gas or chemical sectors, with an understanding of upstream, midstream, downstream, or refining operations.
  • Familiarity with modern data tools (e.g., Snowflake, Databricks, Azure Synapse, Power BI, Tableau).
  • Experience implementing data lakes, Lakehouse architectures, or hybrid data ecosystems.
  • Knowledge of Agile and iterative delivery methodologies.
  • Relevant certifications (e.g., Azure Data Architect, AWS Data Analytics, DAMA CDMP).
Success Metrics
  • Successful delivery of a fully operational enterprise data Lakehouse aligned with business priorities.
  • Measurable improvement in data accessibility, quality, and reporting capabilities.
  • Adoption of data governance and MDM practices across business units.
  • Delivery of a clear project roadmap with defined milestones, timelines, and outcomes.
  • Positive stakeholder feedback on alignment between business needs and technical solutions.
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