Role Description We are looking for a skilled individual to join our rapidly growing team at Bluelight. This position is ideal for someone who thrives in a fast-paced, dynamic environment where everyone's opinions and efforts are valued and appreciated. You will have the opportunity to contribute to challenging and meaningful projects, developing high-quality applications that stand out in the market. We value continuous learning, personal growth, and hard work, offering a collaborative environment that promotes professional development. If you are passionate about software development and eager to be part of a growing software consultancy, we invite you to apply and join us on this exciting journey. - ETL Data Engineering: Develop and maintain ETL data engineering processes using Python (PySpark) within Azure Synapse Analytics Notebooks, and/or Azure Synapse Analytics Pipelines, to ensure efficient data extractions, transformation, and loading. - Data Warehousing: Apply your expertise in data warehousing, understanding star schemas, facts, and dimensions, to design and build effective data storage structures in a Massively Parallel Processing (MPP) SWL Pool. - Data Source Expertise: Extract data from various sources, including REST APIs, SWL database tables, and CSV files. - Azure Synapse Analytics Expertise: Utilize your deep knowledge of Azure Synapse Analytics to design and optimize data notebooks/pipelines for scalability and performance. - Data Fabric Concepts: Contribute to the implementation and understanding of other Data Fabric concepts, such as data lakes, lakehouses, delta lakes, and data cataloging, to enhance data management capabilities. - Data Modeling: Collaborate with data architects to create data models and schemas that align with business requirements. - Data Quality: Implement data quality checks and validation processes to maintain data accuracy and consistency. - Performance Tuning: Identify and resolve performance bottlenecks and optimize ETL data notebooks/pipelines to meet SLAs. - Monitoring and Troubleshooting: Monitor ETL jobs, diagnose issues, and implement solutions to ensure data pipeline reliability. - Documentation: Maintain comprehensive documentation of ETL data engineering processes, data flows, and data transformations. - Collaboration: Work closely with cross-functional teams to understand data requirements and provide support for data-related initiatives. - Security and Compliance: Ensure data security and compliance with data governance and privacy standards. Qualifications - Bachelor’s degree in Computer Science, Information Technology, or a related field; or equivalent work experience, with certifications related to data engineering or data science (e.g. Azure Data Engineer) being a plus. - Proven experience in ETL data engineering with significant expertise in using Python (PySpark) to perform data extraction, transformation, and loading from REST APIs, SQL database tables, and CSV files. - Proficiency in using Azure Synapse Analytics resources including Notebooks, Pipelines, Linked Services, and Azure Key Vault. - Demonstrated ability to write complex SQL queries, optimize query performance, and work with both SparkSQL and MS SQL to effectively extract, transform, and load data. - Knowledge of data integration best practices and tools. - Experience with version control systems, such as Git (Azure DevOps). - Strong problem-solving and analytical skills, with a keen attention to detail. - Excellent communication skills, both verbal and written, with the ability to work collaboratively in a team environment with shifting priorities. - Familiarity with big data technologies, machine learning, and data analysis preferred. - Experience with data visualization tools (e.g. Power BI, Tableau) and Agile Methodologies a plus. Benefits - Competitive salary and bonuses, including performance-based salary increases. - Generous paid-time-off policy. - Flexible working hours. - Work remotely. - Continuing education, training, conferences. - Company-sponsored coursework, exams, and certifications.

Role Description Bull is looking for a proactive Platform Engineer with strong experience in Kubernetes, cloud-native platforms, and distributed infrastructure. The role focuses on resource orchestration platforms, including HPC environments such as Slurm. You will join our international R&D team to help build and operate next-generation cloud and HPC platforms. Key Responsibilities - Design, build, and maintain CI/CD pipelines using Jenkins (Open Source) and GitLab - Deploy and manage applications using Helm and Kustomize - Implement and maintain monitoring and observability solutions using Prometheus, Grafana, and Datadog - Ensure availability, performance, scalability, and reliability of systems - Troubleshoot infrastructure, pipeline, and production incidents - Collaborate with development and operations teams to continuously improve DevOps processes and standards - Automate infrastructure provisioning and configuration using HashiCorp Terraform and Ansible - Support and operate Bull HPC environments, including workload scheduling with Slurm Qualifications - Bachelor’s degree in Computer Science, Software Engineering, or a related technical field - 4+ years of experience building and operating platform infrastructures, preferably based on Kubernetes, virtualization, and Linux environments - Strong experience with Kubernetes administration and ecosystem, including cluster lifecycle management, workload scheduling, networking, and storage - Experience operating multi-cluster Kubernetes environments using tools such as Rancher, Fleet, OpenShift, or similar platforms - Experience with virtualization and infrastructure platforms, including KVM, Proxmox VE, VMware, or similar technologies - Experience operating and troubleshooting Linux-based infrastructure in on-premises or hybrid environments - Experience implementing GitOps workflows using tools such as ArgoCD, FluxCD, or Fleet for infrastructure and application delivery - Knowledge of Infrastructure as Code and configuration management (Terraform, Ansible, Helm, Kustomize, etc.) - Experience with CI/CD pipelines and engineering workflows (Git, Jenkins, GitLab CI, GitHub Actions, etc.) - Experience with observability and monitoring stacks (Prometheus, Thanos, Grafana, Datadog, etc.) - English B2+ minimum. C level desirable Requirements - Experience integrating Kubernetes with HPC schedulers (Slurm integration or hybrid HPC/cloud environments) - Hands-on experience with Kubernetes cluster provisioning and lifecycle automation using Cluster API, Metal3, kubeadm, Kubespray, ClusterAPI providers, or similar technologies - Experience managing Kubernetes on bare-metal infrastructures - Knowledge of Kubernetes security best practices (RBAC, Pod Security Standards, secrets management) - Experience with software-defined networking and load-balancing technologies (HAProxy, Keepalived, VLAN/VXLAN, MetalLB, etc.) - Any previous experience in innovation and pre-sales departments or in European research projects is valuable Benefits - Flexible Work Schedule: Enjoy half-day Fridays and an intensive summer workday to help maintain a great work-life balance - Learning & Growth: Stay at the forefront of AI and technologies, with opportunities to learn and grow in a supportive, innovative environment

• Own 5 AWS accounts across the organisation (QA, Prod, Infra, plus two others) • Architect and maintain infrastructure as code with Terraform. • Replace the click-ops that's still around • Stand up CI/CD pipelines engineers actually want to use. Blue/green and canary where it makes sense • Run releases reliably and reduce key-person risk on the deploy process • Set up monitoring, alerting, and incident response so we catch issues before customers do. • Define SLIs and SLOs that map to real user journeys • Lead incident response as the primary infra responder. Run blameless post-mortems • Patch and harden the platform. We're a fintech, this matters. IAM least privilege, secrets management, vulnerability scanning, MFA enforcement • Lead infrastructure work for the TV launch: traffic spikes, autoscaling, capacity planning, runbooks • Partner with backend engineers when production issues cross into the app tier. JVM tuning, connection pools, async patterns, memory leaks • Architect multi-region DR. • Drive the platform toward self-healing • Optimise cost across DynamoDB, Lambda, and the wider AWS footprint • Set architectural guardrails with tech leads and SWEs. • Mentor engineers as the platform capability grows.

• Help build the next generation of our data platform, a streaming-first, domain-oriented foundation • Work on infrastructure, tooling, and paved paths for data flow from production systems • Enable near real-time access for analysts, engineers, AI systems, and business users • Champion platform standards, tooling, and best practices across the data organization