IT Director - Data Management

Role summary

Seeking a senior data & analytics leader to own the enterprise data strategy, platforms, and partnerships that turn operational data into measurable business outcomes. The ideal candidate blends strong business acumen with deep technical expertise to meet today’s analytics needs and accelerate use cases in AI and large language models.

Responsibilities

Stakeholder leadership

• Build trusted partnerships across Geoscience, Engineering, Drilling, Completions, Finance, Accounting, HR, and Operations to convert data into decisions and ROI.

• Coach leaders and teams on how modern data platforms and AI can improve safety, productivity, and capital efficiency.

• Advocate for data as a strategic asset and align investments to clear operational and financial results.

• Hire, mentor, and lead a high-performing team of data engineers, analytics engineers, automation specialists, analysts, and data scientists.

Platform & Architecture Ownership

• Lead the design, implementation, and optimization of the enterprise data stack: Databricks, Dagster, dbt, Power BI, and Spotfire.

• Own the lakehouse / warehouse / data mart ecosystem; ensure resilient pipelines, governed models, and performant semantic layers.

• Integrate data across enterprise applications and services; drive automation, near-real-time availability, cost/performance tuning, and reliability.

AI & Advanced Analytics

• Evaluate and implement ML and LLM capabilities to enhance analytics, reporting, search/knowledge management, and natural-language interfaces.

• Enable predictive and prescriptive insights (e.g., equipment reliability, production optimization) and embed them into workflows.

Governance & Quality

• Establish the enterprise data catalog and metadata practices; lead data governance forums and policies.

• Drive data quality, lineage, and consistency standards with automated monitoring and remediation.

Qualifications

• 12+ years in data analytics, BI, or related fields; 10+ years in leadership/management.

• Deep familiarity with upstream oil & gas data domains and operational challenges.

• Proven success building and leading technical teams in complex, enterprise environments.

• Expert understanding of lakehouse architecture, dimensional/enterprise data modeling, and modern ELT patterns.

• Hands-on experience with Databricks, Dagster, dbt, Power BI, and Spotfire.

• Strong command of SQL, ETL/ELT, data pipeline automation, and integration patterns (batch/streaming, APIs).

• Proficiency in Python (and/or R) for platform development, orchestration, and automation.

• Experience with cloud-scale data platforms and the modern data stack.

• Expertise in data governance, metadata management, lineage, and data quality tooling and processes.

• Ability to lead through influence in matrixed settings; exceptional communication skills for technical and business audiences.

• Track record of elevating data literacy and instituting best practices across an organization.