Senior Data Engineer - 1S6J022
At a glance
Senior Data Engineering role at SNIPEBRIDGE. Dallas · full-time · no salary stated · we estimate $142,500–$193,650 across the United States.
SNIPEBRIDGE has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Build and operate scalable batch and streaming pipelines, then test them for dependable delivery
- Bring together operational technology, monitoring, asset, energy, financial and enterprise data
- Create curated models and reusable datasets for analytics, reporting, forecasting and machine learning
- Strengthen data quality, observability, lineage, documentation and incident response across the data lifecycle
- Tune storage, orchestration, query performance, reliability and cloud costs while mentoring engineers and reviewing code
What you bring
- At least six years in data engineering, analytics engineering or backend platform work
- A bachelor's degree in computer science, engineering, information systems or a related area, or equivalent experience
- Advanced SQL and Python ability, with a record of building production-ready pipelines
- Background with a major cloud environment and current data services, warehouses or lakehouse technologies
Who this fits
This senior, hands-on role suits someone who can contribute to architecture, guide engineers and work with analysts, software engineers and operations leaders. The job is onsite in Dallas. You must already hold long-term U.S. work authorization and be legally able to work in the United States without sponsorship.
From the employer
SNIPEBRIDGE is a strategic talent solutions company specializing in connecting exceptional talent to great career opportunities. We work as an exclusive partner to leading AEC and technology organizations that are advancing the built environment through innovation, technical rigor, and transformative work.
COMPANY
Our client operates within the fast-moving data center and digital infrastructure sector, where engineering, construction, technology, energy, and operations come together to support always-on environments. Its multidisciplinary teams plan, design, deliver, and operate complex facilities with a strong focus on reliability, safety, scalability, and efficient use of power and cooling. The work calls for close coordination across technical disciplines and offers the opportunity to contribute to infrastructure that supports the continued growth of cloud computing, AI, and connected services.
THE OPPORTUNITY
The Senior Data Engineer will build the trusted data foundation used to understand infrastructure performance, capacity, energy, maintenance, and business operations. The role combines hands-on engineering with architecture and partnership, turning data from multiple operational systems into reliable, governed, and usable products.
KEY RESPONSIBILITIES
- Design, build, test, and operate scalable batch and streaming data pipelines
- Integrate data from operational technology, monitoring, asset, energy, financial, and enterprise platforms
- Develop curated data models and reusable datasets for analytics, reporting, forecasting, and machine learning
- Establish data-quality checks, observability, lineage, documentation, and incident-response practices
- Optimize storage, orchestration, query performance, reliability, and cloud cost
- Partner with analysts, software engineers, operations leaders, and subject-matter experts to define data products
- Review code, mentor engineers, and improve engineering standards and deployment practices
- Apply security, privacy, access-control, and governance requirements throughout the data lifecycle
REQUIREMENTS
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience
- 6+ years of data engineering, analytics engineering, or backend platform experience
- Advanced SQL and Python skills with experience building production-grade pipelines
- Experience with a major cloud platform and modern data services, warehouses, or lakehouse technologies
- Working knowledge of orchestration, transformation, version control, CI/CD, testing, and data observability
- Experience with Spark, Databricks, Kafka, dbt, Airflow, or comparable technologies preferred
- Strong system-design, troubleshooting, documentation, and stakeholder communication skills
All applicants must be legally authorized to work in the United States without sponsorship and must already possess long-term work authorization.
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