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CB&I

Data Engineer

The Woodlands, TX, United States

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Job details

Apply by: Nov 4, 2027
Experience: 15 years of general data and application experience, 10+ years specifically in data engineering, including hands-on work with ETL/ELT processes, data modeling, and cloud platforms.
Posting language: English
Posted: Nov 4, 2026

Original job description

Company Overview

CB&I delivers integrated storage and asset‑management solutions that help customers operate safely, reliably, and efficiently across the lifecycle of their facilities. Through our two global business units - Storage Solutions, the world leader in tanks, terminals, and storage systems, and Asset Solutions, a leading provider of operations, management, wells and decommissioning services - we combine technical excellence with execution capability to extend asset life, optimize performance, and maximize value.

Overview

The Data Engineer is responsible for designing, developing, integrating, and optimizing enterprise data platforms, pipelines, and data models that support reporting, analytics, automation, and AI initiatives. This role directly reports to the Director, Applications and Data Management and routinely interacts with Global IT, Global Business Leads, Global Functional Leads, and Project Management.

Responsibilities

Establish and assess organizational data management requirements to select and implement suitable data platform technologies.
Lead the design of robust, scalable, and efficient data pipelines, setting the example for data architecture and engineering standards across various data sources.
Establish best practices for data quality and security to drive enterprise data integration strategies.
Collaborate with infrastructure and cybersecurity teams to architect and secure the data infrastructure.
Work closely with data analysts and business stakeholders to understand data needs, provide clean and reliable datasets, and support machine learning and analytics initiatives.
Establish and optimize data systems for performance, scalability, and cost-efficiency; troubleshoot and resolve data pipeline issues in a timely manner.
Design and implement data models (e.g., star schema, dimensional models) to support reporting and analytics requirements.
Automate repetitive data processes to improve efficiency and reduce manual intervention.
Create and maintain detailed documentation for data pipelines, processes, and system architectures.
Serve as a key advisor on data governance, regulatory compliance, data stewardship, and risk management practices.
Provide technical leadership across multiple initiatives and influence larger, long-term projects.

Qualifications

A bachelor’s degree in computer science, data engineering, information systems, or equivalent work experience required. Master’s degree in computer science, data engineering, or information systems preferred.
15 years of general data and application experience, 10+ years specifically in data engineering, including hands-on work with ETL/ELT processes, data modeling, and cloud platforms.
Strong expertise in programming languages (e.g., Python, Java, C#).
Strong expertise querying databases with SQL.
Extensive experience with data pipeline tools (e.g., Informatica, Azure Data Factory, Apache Kafka).
Experience with database management systems (e.g. SQL Server, Oracle, MongoDB).
Expertise in architecting cloud data platforms (e.g. Snowflake, Microsoft Synapse, Databricks).
Familiarity with reporting and visualization tools (e.g. PowerBI, Tableau, Business Objects).
Demonstrated experience delivering data engineering projects in a team setting.
Demonstrated ability to communicate clearly and concisely, both orally and in writing, and lead presentations, training courses, and effective meetings.
Experience managing service provider relationships (e.g. data engineering consultants, cloud data platform vendors).
Experience in the Architecture, Engineering and Construction industry a plus.
Relevant data engineering certifications preferred.

Skills and Behaviors

Expertise in data engineering, integration, and data architecture best practices.
Knowledge of data modeling, data warehousing, and master data management principles.
Ability to design scalable, secure, and reliable data solutions.
Proficiency with cloud data platforms, databases, APIs, and ETL/ELT technologies.
Strong understanding of data governance, security, privacy, and compliance requirements.
Ability to analyze complex technical challenges and implement effective solutions.
Experience leading cross-functional initiatives and collaborating with business and technology stakeholders.
Commitment to continuous improvement, automation, and technical excellence
Proactively embraces and promotes the company’s values and culture, including a healthy and safe work environment.

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