Job Title: IT Data Analytics Director
Req Id: 12804
Specific ResponsibilitiesThe 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 & ExperienceThe 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.
CompetenciesThe 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.
