Martin Laur

Led cloud infrastructure and DevSecOps engineering for data-intensive compliance services, defining technical direction and maintaining secure production environments using AWS, Terraform (IaC), Python, and Linux. Designed and maintained reusable Terraform modules for EC2, S3, IAM, RDS, Lambda, and VPC networking to enable consistent provisioning. Built infrastructure for structured and unstructured data workflows using S3, RDS/PostgreSQL, and AWS Glue for ingestion, processing, storage, and analytics. Drove architecture decisions around IAM policies, encryption, network segmentation, and access controls for sensitive data. Implemented production monitoring, centralized logging, metrics, and alerting with CloudWatch to improve operational visibility. Developed deployment automation and CI/CD workflows using Git, GitHub, Docker, Python, and shell scripting to support repeatable releases across development and production. Partnered with data engineers, software engineers, and stakeholder

Led infrastructure engineering for a distributed software platform, designing reliable cloud environments using AWS, Linux, Docker, and IaC practices. Built reusable provisioning workflows with Terraform to standardize infrastructure creation across development, testing, and production. Managed key cloud and networking components including EC2, S3, IAM, RDS, and VPC networking with focus on controlled access, network isolation, reliability, and maintainability. Designed CI/CD workflows using Git, GitHub, Jenkins, Docker, and scripting for build, validation, packaging, and deployment of application and infrastructure changes. Administered production Linux environments, performing installation, configuration, performance tuning, troubleshooting, security hardening, user administration, and automation with Bash and Python. Implemented monitoring, logging, health checks, and alerting patterns for distributed infrastructure. Designed database infrastructure around PostgreSQL, MySQL, Redis,

Developed Python services and data-processing workflows supporting machine learning and data-intensive application features, integrating structured and unstructured datasets into repeatable processing pipelines. Built infrastructure and deployment automation using Linux, Python, Bash, version control, and CI/CD to create reliable development and production environments. Designed data storage and integrations using PostgreSQL, MySQL, Redis, and Elasticsearch to support search, analytics, and ML workloads. Containerized services with Docker and implemented repeatable build/deployment processes for Python workloads. Created operational scripts in Python and Bash to automate environment configuration, service management, validation, backup operations, and recurring infrastructure tasks. Administered Linux systems for package installation, monitoring, troubleshooting, user management, and security. Collaborated with engineering and data teams to identify tooling needs for pipelines, deploym