Senior Data Engineer II

Hybrid role in Irving, TX with a competitive salary range and a focus on building reliable data pipelines and ML-enabled services. This position supports daily data operations, complex data engineering bug resolution, and designing advanced data models and ETL workflows, while also contributing to machine-learning application development and deployment in multiple development environments. You will also mentor junior engineers and help drive process improvements.

What you will do

• Perform daily data loads, ensuring recurring updates are logged and tracked.
• Coordinate with technical stakeholders to document, interpret, and finalize requirements for development.
• Develop efficient, repeatable code that avoids defects and follows best practices including naming conventions and encapsulation.
• Write and review portions of detailed specifications for system components of moderate complexity.
• Complete complex data engineering bug fixes and resolve related issues by researching and identifying root causes.
• Collaborate with other development team members to translate complex product requirements into data engineering and/or data management designs.
• Contribute to process improvements that enable efficient delivery and ongoing maintenance.
• Apply development processes, coding best practices, and code review practices.
• Operate in multiple development environments, including Agile and Waterfall, while partnering with key stakeholders.
• Identify opportunities to work with other teams and peers to improve overall quality and efficiency, and implement initiatives that strengthen capabilities.
• Train entry-level data engineers as directed and mentor junior engineers on methodologies and optimization techniques.
• Keep current with new technology developments.
• Design and work with complex data models.
• Perform other duties as needed.

Qualifications

• Bachelor’s degree (or foreign equivalent) in Computer Science, Computer Engineering, Information Systems, or a related field.
• 5 years of experience in the job offered or related occupations.
• 5 years of experience with ML-based application development and API integration to build features that rely on machine-learning models, integrate models via APIs to send data and receive predictions automatically, and convert research-grade models into stable, scalable services.
• 5 years of experience with data engineering and ETL pipelines to design automated workflows that extract, transform, and load data from multiple sources into databases or ML systems, including cleaning, validation, and reliable delivery of large volumes of structured and unstructured data.
• 5 years of experience utilizing database and vector store technologies, including SQL/NoSQL databases and vector databases such as Solr, Elasticsearch, or Pinecone.
• 5 years of experience with cloud infrastructure, deployment automation, and containerization, including deploying on AWS, Azure, and GCP using Terraform and Docker.
• 5 years of experience using Kubernetes to manage, deploy, and scale containerized applications across multiple servers with availability, recovery, and safe rollback capabilities.
• 5 years of experience with MLOps and model deployment, including deploying ML models using orchestration tools such as KubeRay and Triton Inference Server (or similar).

Technologies

• ML-Based Application Development, API Integration, machine-learning models
• ETL Pipelines
• Solr, Elasticsearch, Pinecone
• SQL, NoSQL, vector databases
• AWS, Azure, GCP, Terraform, Docker
• Kubernetes
• MLOps, KubeRay, Triton Inference Server
• Agile, Waterfall

Benefits

• Standard company benefits
• Country-specific benefits

Compensation

Salary range for REQ# R119869: $160,285.00 to $174,600.00/year + standard company benefits.

U.S. national base pay range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates.

How to apply

Send an email to [email protected] and reference job code: R119869.