Job description

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.

Requirements

Must-haves

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
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
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.

Nice-to-haves

Experience with Spark, Databricks, Kafka, dbt, Airflow, or comparable technologies preferred

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningsqlpythonci/cd

Platform: workable
Effort: medium