Python Data Engineer

Python Data Engineer

Posted 1 week ago by Robert Walters

Negotiable
Undetermined
Undetermined
Glasgow, Scotland, United Kingdom

Summary: The Python Data Engineer role focuses on developing tooling and self-service capabilities for deploying AI solutions, enhancing the developer experience, and building scalable Generative AI use cases. The position requires collaboration with other developers and involves leveraging modern technologies such as Kubernetes and container registries. Key responsibilities include authoring best practices, analyzing GenAI solutions, and ensuring the reliability and scalability of AI platforms. The role demands a strong application development background and experience in data engineering and cloud-native applications.

Key Responsibilities:

  • Develop tooling and self-service capabilities for deploying AI solutions.
  • Collaborate with developers to enhance the developer experience for AI applications.
  • Build common, reusable solutions for Generative AI use cases using pre-trained and fine-tuned models.
  • Leverage Kubernetes/OpenShift for modern containerized workloads.
  • Utilize container registries and configuration management technologies for workload management.
  • Integrate with large-scale vector stores for embeddings.
  • Author best practices on the Generative AI ecosystem and available models.
  • Analyze and implement GenAI solutions focusing on Agentic Orchestration and Agent Builder frameworks.
  • Contribute to design decisions and product selection for Generative AI solutions.
  • Ensure AI platforms are reliable, scalable, and operational.
  • Participate in Agile/Scrum ceremonies.

Key Skills:

  • Strong hands-on Application Development background in Python Flask or FAST API.
  • Broad understanding of data engineering (SQL, NoSQL, Big Data, Kafka, Redis).
  • Experience in Kubernetes workload management, preferably on OpenShift.
  • Experience in designing and managing RESTful services for enterprise solutions.
  • Hands-on experience with multiprocessing, multithreading, and performance profiling in Python.
  • Practitioner of unit testing, performance testing, and BDD/acceptance testing.
  • Understanding of OAuth 2.0 protocol for secure authorization.
  • Proficiency with Open Telemetry tools (Grafana, Loki, Prometheus, Cortex).
  • Demonstrated experience in DevOps and understanding of CI/CD (Jenkins) and GitOps.
  • Ability to articulate technical concepts to diverse audiences.
  • Strong desire to influence development teams to adopt AI.
  • Understanding of deep learning and Machine Learning frameworks (TensorFlow, PyTorch).
  • Experience in building cloud and container-native applications.
  • Excellent communication skills.

Salary (Rate): undetermined

City: Glasgow

Country: United Kingdom

Working Arrangements: undetermined

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

Primary Responsibilities Develop tooling and self-service capabilities for deploying AI solutions for the firm. Collaborate with other developers to enhance the developer experience when building and deploying AI applications. Have a platform mindset and build common, reusable solutions to scale Generative AI use cases using pre-trained models as well as fine-tuned models. Leverage Kubernetes/OpenShift to develop modern containerized workloads. Leverage container registries like JFrog artifactory, container packaging/configuration management technologies like Helm & Kustomize, and GitOps deployment methods to orchestrate, manage and deploy these workloads. Integrate with capabilities such as large-scale vector stores for embeddings. Author best practices on the Generative AI ecosystem, when to use which tools, available models such as GPT, Llama, Hugging Face etc. and libraries such as Langchain. Analyze, investigate, and implement GenAI solutions focusing on Agentic Orchestration and Agent Builder frameworks. Contribute to major design decisions and product selection for building Generative AI solutions. Inclusive of app authentication, service communication, state externalization, container layering strategy and immutability. Ensure AI platform are reliable, scalable, and operational; (e.g. blueprints for upgrade/release strategies (E.g. Blue/Green); logging/monitoring/metrics; automation of system management tasks) Participate in all team's Agile/ Scrum ceremonies. Required Skills Strong hands-on Application Development background in at least one prominent programming language, preferably Python Flask or FAST Api. Broad understanding of data engineering (SQL, NoSQL, Big Data, Kafka, Redis), data governance, data privacy and security. Experience in development, management, and deployment of Kubernetes workloads, preferably on OpenShift. Experience with designing, developing, and managing RESTful services for large-scale enterprise solutions. Hands-on experience with multiprocessing, multithreading, asynchronous I/O, performance profiling in at least one prominent programming language, preferably python. Practitioner of unit testing, performance testing and BDD/acceptance testing. Understanding of OAuth 2.0 protocol for secure authorization. Proficiency with Open Telemetry tools including Grafana, Loki, Prometheus, and Cortex. Demonstrated experience in DevOps, understanding of CI/CD (Jenkins) and GitOps. Ability to articulate technical concepts effectively to diverse audiences. Strong desire and ability to influence development teams and help them adopt AI. Demonstrated ability to work effectively and collaboratively in a global organization, across time zones, and across organizations. Understanding of deep learning, understanding of Machine Learning frameworks such as TensorFlow or PyTorch. Understanding of Information Security, Secure coding practices. Experience in building cloud and container native applications. Knowledge of DevOps and Agile practices. Excellent communication skills. Desired Skills Good knowledge of Microservice based architecture, industry standards, for both public and private cloud. Good understanding of modern Application configuration techniques. Hands on experience with Cloud Application Deployment patterns like Blue/Green. Good understanding of State sharing between scalable cloud components (Kafka, dynamic distributed caching). Good knowledge of various DB engines (SQL, Redis, Kafka, etc) for cloud app storage. Experience building AI applications, preferably Generative AI and LLM based apps. Deep understanding of AI agents, Agentic Orchestration, Multi-Agent Workflow Automation, along with hands-on experience in Agent Builder frameworks such Lang Chain and Lang Graph. Experience working with Generative AI development, embeddings, fine tuning of Generative AI models. Understanding of ModelOps/ ML Ops/ LLM Op. Understanding of SRE techniques. Qualifications: Bachelor's or Master's degree in Computer Science or related field, or equivalent job experience 5 years of experience in software engineering, design and development We are committed to offering an inclusive recruitment experience. If you require accommodations because of disability or health condition, please email: gscemeaedi @ robertwalters.com. This position is being sourced through our Outsourcing service line.