Data Operations Engineer – GCP / Python / DevOps
Data Operations Engineer – GCP / Python / DevOpsLocation: Remote – East Coast Preferred
Schedule: Core Business Hours (EST/CST)
Pay: $80-85 hourly
Employment Type: W-2 Contract
Contract Duration: Potential for Extension
Work Authorization:
Must be authorized to work in the U.S. without sponsorship, now or in the future. 3rd party applicants will not be considered.
Position Overview:
Alphanumeric Systems is seeking an experienced Data Operations Engineer to support the Onyx Data and Knowledge Platforms Group within a leading global pharmaceutical organization. This team is building a next-generation, cloud-native research data platform designed to accelerate scientific discovery through advanced data engineering, automation, and AI/ML capabilities. We are looking for a technically strong, hands-on engineer with expertise in cloud infrastructure development, Python software engineering, and DevOps practices. The ideal candidate is more than a task executor. We're seeking a proactive problem-solver who can identify technical challenges, recommend solutions, contribute to backlog development, and independently drive initiatives from concept through delivery. This role offers the opportunity to work with a collaborative, distributed engineering team developing scalable infrastructure and DataOps solutions that support scientific research and innovation.
What You'll be Doing:
Design, develop, and maintain scalable, cloud-native infrastructure and software solutions supporting enterprise research data platforms.
Build and enhance cloud infrastructure, preferably within Google Cloud Platform (GCP).Develop high-quality software, automation tools, and services using Python or similar programming languages.
Implement and support DevOps practices, including CI/CD pipelines, infrastructure automation, monitoring, and operational reliability.
Collaborate with data engineering, infrastructure, DevOps, and software development teams to deliver integrated platform solutions.
Translate loosely defined business and technical challenges into actionable solutions and technical specifications.
Proactively contribute ideas, recommend improvements, and participate in sprint planning and backlog development.
Develop reusable tools, workflows, and automation to improve data platform scalability, performance, and efficiency.
Apply software engineering best practices, including code reviews, automated testing, documentation, and version control.
Support cloud infrastructure optimization, troubleshooting, and continuous improvement.
Ensure solutions align with established standards for security, data governance, logging, and operational reliability.
Collaborate effectively with remote team members and provide technical guidance when needed.
Required Qualifications:
5+ years of relevant experience in software engineering, cloud infrastructure development, DevOps, or DataOps.
Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
Strong experience developing and supporting cloud-based infrastructure and applications; Google Cloud Platform (GCP) preferred.
Strong software engineering and programming experience; Python preferred.
Solid understanding of the Software Development Lifecycle (SDLC), including design, development, testing, deployment, and maintenance.
Experience with DevOps methodologies, automation, and CI/CD practices.
Familiarity with cloud-native architectures, scalable systems, and infrastructure management.
Strong troubleshooting, analytical, and problem-solving capabilities.
Ability to work independently, take ownership of technical initiatives, and deliver solutions with minimal oversight.
Excellent communication and collaboration skills within a distributed Agile development environment.
Preferred Qualifications:
- Experience with Infrastructure as Code (IaC) tools such as Terraform.
- Experience working with data engineering platforms, DataOps frameworks, or enterprise data infrastructure.
- Familiarity with containerization technologies such as Docker and Kubernetes.
- Experience developing or supporting infrastructure for AI/ML, data science, or advanced analytics environments.
- Knowledge of cloud monitoring, logging, observability, and performance optimization.
- Experience supporting large-scale data platforms or complex data integration environments.
- Exposure to pharmaceutical, biotechnology, life sciences, or scientific research environments.
- Experience mentoring junior engineers or contributing to engineering best practices.
- What Makes Someone Successful in This Role?
- We're particularly interested in engineers who demonstrate:
- Technical Ownership: Ability to independently develop solutions from initial concept through production.
- Proactive Problem-Solving: Willingness to identify opportunities, propose ideas, and improve existing systems.
- Strong Engineering Fundamentals: Commitment to maintainable code, automation, testing, and documentation.
- Collaborative Mindset: Ability to contribute effectively within a remote, cross-functional Agile team.
- Adaptability: Interest in emerging technologies, cloud infrastructure, and modern data engineering practices.
Employment Requirements:
Direct W-2 applicants only. No C2C arrangements or third-party agency submissions.
Candidates must be authorized to work in the United States without employer sponsorship, now or in the future.
Must be available to work core EST/CST business hours.
Remote position; candidates located on the East Coast are preferred.
Interested in Learning More?
If you're a cloud-focused software engineer with strong Python, GCP, and DevOps experience who enjoys solving complex technical challenges, we'd love to hear from you.
Apply today or connect with Alphanumeric Systems to learn more about this opportunity.