Senior Data Engineer

Salas O’Brien | Digital & AI

Reports To: Director, Data Engineering & Architecture
Location: Remote (United States)
Travel: Up to 10%
Compensation: $120,000-$140,000 base salary, eligible for performance bonus

About Salas O’Brien

At Salas O’Brien, we tell our clients that we’re engineered for impact. This passion for making a difference applies just as much to our team as it does to our projects. That’s why we’re committed to living our values every day: inspiring, achieving, and connecting as shared owners of our success with a focus on a sustainable future.

Building for the long term means that all of our team members can expect to work on meaningful projects with a people-first approach to problem-solving. It also means each team member has limitless potential to build a unique, high-impact career while sharing in our collective success.

Founded in 1975, Salas O’Brien is an employee-owned engineering and professional services firm focused on achieving impact for our clients, our team members, and the world. We provide integrated engineering, consulting, and technical services across a wide range of industries, including healthcare, data centers, science and technology, education, infrastructure, energy, and the built environment.

As one of the fastest-growing engineering firms in North America, Salas O’Brien continues to grow through strategic acquisitions, innovation, and operational excellence. Our Digital & AI organization is building enterprise capabilities that transform how data is managed, analyzed, and leveraged to support business performance and future growth.

Job Summary

The Senior Data Engineer is responsible for designing, building, and maintaining the enterprise data infrastructure that powers analytics, reporting, artificial intelligence, and operational decision-making across Salas O’Brien. This role serves as a key contributor within the Data Engineering & Architecture team and is responsible for transforming data from diverse business systems into trusted, scalable, and accessible enterprise data products.

As Salas O’Brien continues to expand through acquisitions and digital transformation initiatives, the Senior Data Engineer will play a critical role in integrating new data sources, improving data quality, and delivering scalable solutions that support enterprise growth. This position partners closely with Data & Information Architects, Data Governance professionals, AI engineers, analysts, and business stakeholders to ensure enterprise data assets are secure, reliable, and aligned with business needs.

This role is ideal for a hands-on engineer who enjoys solving complex integration challenges, building modern cloud-based data solutions, and creating high-quality data products that drive business value.

What Success Looks Like

Builds and maintains reliable data pipelines, integrations, and enterprise data infrastructure that transform fragmented source systems into trusted business assets. Delivers scalable, well-documented, and high-quality data products that support reporting, analytics, operational decision-making, and AI initiatives.

Success is measured through:

• Reliable and trusted enterprise data products used across the organization.
• Successful onboarding and integration of new business systems and acquired entities.
• Improved data quality, accessibility, and consistency across platforms.
• Strong platform performance, scalability, and operational reliability.
• Effective partnership with architects, governance leaders, and business stakeholders.
• Delivery of enterprise data solutions that accelerate reporting, analytics, and AI capabilities.

Responsibilities

Enterprise Data Pipeline Development

• Design, develop, and maintain scalable data pipelines that support enterprise reporting, analytics, and AI workloads.
• Integrate data from a variety of business systems including ERP, CRM, HRIS, Deltek Vantagepoint, SharePoint, financial systems, and engineering applications.
• Develop ingestion, transformation, and data delivery processes that support enterprise business requirements.
• Build and maintain data workflows that support both batch and near real-time processing needs.
• Ensure data pipelines are reliable, maintainable, and scalable as business demands evolve.

Data Platform Engineering

• Develop and support enterprise lakehouse and cloud-based data platforms.
• Implement data storage, processing, and transformation solutions that support enterprise analytics and AI initiatives.
• Optimize data performance, scalability, and resource utilization.
• Support metadata management, lineage tracking, and enterprise data catalog capabilities.
• Participate in platform architecture discussions and technical design reviews.

Data Quality & Reliability

• Implement data quality controls, validation processes, and monitoring solutions.
• Identify and resolve data integrity issues across enterprise systems.
• Develop automated testing and observability capabilities to improve platform reliability.
• Monitor data pipeline performance and proactively address issues before they impact business operations.
• Maintain documentation supporting enterprise data products and processes.

Data Modeling & Integration

• Collaborate with Data & Information Architects to implement enterprise data models and master data strategies.
• Support development of enterprise business entities and authoritative data sources.
• Implement integration standards and patterns that promote consistency across platforms.
• Assist with onboarding and integration of acquired companies and business units.
• Support development of enterprise data products used by business and technical teams.

Governance, Security & Compliance

• Implement governance controls within enterprise data pipelines and platforms.
• Support data classification, retention, lineage, access management, and audit requirements.
• Partner with Data & AI Governance leaders to ensure compliance requirements are operationalized through technology.
• Support secure handling of sensitive business and client information.
• Maintain documentation supporting governance and compliance initiatives.

AI, Analytics & Business Enablement

• Partner with AI engineers, analysts, and business stakeholders to understand data requirements.
• Develop data assets that support machine learning, automation, and advanced analytics initiatives.
• Support self-service analytics and reporting capabilities across the organization.
• Ensure enterprise data products are designed to support current and future business needs.
• Participate in innovation initiatives that leverage enterprise data capabilities.

Team Collaboration & Continuous Improvement

• Contribute to engineering standards, best practices, and documentation.
• Participate in code reviews, architecture discussions, and technical planning sessions.
• Share knowledge and mentor junior team members as the organization grows.
• Identify opportunities to improve processes, automation, and engineering efficiency.
• Promote a culture of collaboration, accountability, and continuous learning.

Qualifications & Experience

Required

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or a related discipline.
• 6+ years of professional data engineering experience.
• Strong experience designing, developing, and supporting production data pipelines.
• Advanced proficiency in SQL and Python.
• Experience working with cloud-based data platforms and enterprise data environments.
• Experience integrating multiple business systems and data sources.
• Strong understanding of:
• Data engineering principles
• Data modeling
• ETL/ELT development
• Data quality management
• Enterprise reporting and analytics
• Experience working with large datasets and complex data structures.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Authorization to work in the United States without sponsorship.

Preferred

• Experience with Databricks, Delta Lake, Azure Data Services, Microsoft Fabric, or comparable cloud platforms.
• Experience with graph databases such as Neo4j or similar technologies.
• Experience supporting enterprise analytics, AI, and machine learning initiatives.
• Familiarity with master data management and enterprise data architecture concepts.
• Experience integrating systems in acquisition-driven or highly decentralized organizations.
• Knowledge of governance and compliance frameworks including NIST, SOC 2, CMMC, GDPR, or HIPAA.
• Professional services, engineering, construction, or consulting industry experience.
• Experience mentoring junior engineers or leading technical initiatives.

Travel

Travel up to 10% may be required to support team collaboration, strategic planning sessions, acquisition integration activities, stakeholder meetings, and Digital & AI team events.

Compensation & Benefits

The expected base salary range for this role is $120,000-$140,000 USD annually. Actual compensation will be determined based on skills, experience, qualifications, and geographic location.

This role is also eligible for performance-based incentive compensation, equity participation, and a comprehensive benefits package that includes:

• Medical, dental, and vision insurance
• 401(k) with company match
• Paid time off and company holidays
• Wellness programs and employee assistance resources
• Professional development and learning opportunities
• Employee ownership participation
• Additional benefits consistent with Salas O’Brien policies

Equal Opportunity Employment Statement

Salas O’Brien provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, colour, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state/provincial, or local laws.

Salas O’Brien will accommodate the disability-related needs of applicants as required by law.