AWS
Our AWS Solutions Include:
At PulseTech, our AWS specialists help you design, build, secure, and operate cloud infrastructure across the full breadth of Amazon Web Services, from architecture and DevOps to data, machine learning, networking, and security. Whether you need an AWS Solutions Architect designing a scalable cloud foundation, an AWS Security Specialist hardening your environment, an AWS Data Engineer building analytics pipelines, or an AWS Cloud Consultant guiding your migration strategy, our team brings deep platform expertise to every engagement. Explore the roles below to see how each one supports your AWS journey.
AWS Solutions Architects design cloud solutions that take full advantage of AWS's broad, flexible infrastructure, allowing workloads to scale dynamically as demand changes rather than being constrained by fixed capacity. Security and compliance are built into these designs from the start, using AWS's advanced security features to protect data and meet the regulatory requirements relevant to your industry. They also focus on optimisation, making sure the services chosen for a given workload deliver strong performance without unnecessary cost, and that the overall architecture stays efficient as it grows. Beyond individual projects, they think strategically, developing cloud solutions that align with where the business is headed, not just where it is today. Day to day, this means designing scalable and flexible cloud architectures suited to your needs, ensuring data and application security through AWS's security services, optimising costs using AWS pricing models and tools, and integrating various AWS services into your business processes to increase operational efficiency.
AWS DevOps Engineers bring automation and continuous delivery practices to bear on AWS infrastructure, building pipelines that take code from commit to production reliably and with minimal manual intervention. They set up monitoring across applications and infrastructure, using AWS's observability tools to catch performance issues early and keep systems running smoothly. A central goal is fast, dependable deployment, so new features and fixes can reach users quickly without introducing instability. By integrating development, testing, and deployment into a single continuous workflow, they help teams release more often with greater confidence. In practice, this means designing and implementing continuous integration and delivery processes on AWS, automating workflows with services like AWS CodePipeline and CodeBuild, monitoring and improving application performance with AWS CloudWatch and X-Ray, and building secure, compliant DevOps processes by integrating AWS's security services throughout the pipeline.
AWS Cloud Engineers manage the infrastructure that AWS-based applications run on, configuring and maintaining resources so workloads run efficiently and reliably. They build infrastructure that's both secure and highly accessible, applying AWS's security tools and best practices so systems stay protected without becoming difficult to work with. A key part of the role is enabling fast deployment and dynamic scalability, so infrastructure can expand or contract automatically as demand changes rather than requiring manual intervention. They also keep a close eye on resource usage, managing AWS resources to balance cost and performance over time. Day to day, this means managing infrastructure as code with tools like AWS CloudFormation and Terraform, implementing AWS security services and policies to maintain compliance, scaling workloads using services like Amazon EC2 Auto Scaling and Elastic Load Balancing, and ensuring data integrity through backup and disaster recovery plans built with AWS Backup and related solutions.
AWS Data Engineers build the pipelines and infrastructure that turn raw data into something the business can actually use, processing large datasets quickly and efficiently using AWS's big data services. They set up the analytics tooling that lets teams dig into that data and surface insights that support better decision-making across the organisation. For use cases where timing matters, they build systems capable of analysing data streams as they arrive, enabling decisions to be made in near real time rather than after the fact. They also bring together data from multiple sources into coherent, well-structured solutions, so disparate systems don't end up as isolated data silos. In practice, this means building big data solutions with services like Amazon EMR and AWS Glue, storing and analysing data with data warehousing services like Amazon Redshift, processing real-time data streams with Amazon Kinesis and AWS Lambda, and automating and optimising data integration processes with AWS Data Pipeline and AWS Glue.
AWS Security Specialists focus on protecting data and applications running on AWS, applying advanced security services to guard against a wide range of threats. They help organisations meet legal and industry compliance requirements, using AWS's compliance tooling to demonstrate that controls are in place and working as intended. A major part of the role is threat detection and response, watching for suspicious activity across an AWS environment and acting quickly when something needs attention. To keep this manageable at scale, they automate as much of the security workload as possible, so consistent checks happen continuously rather than relying on periodic manual reviews. Day to day, this means creating and implementing security policies with AWS Identity and Access Management (IAM), monitoring and analysing threats with Amazon GuardDuty and AWS Security Hub, meeting compliance requirements using AWS Artifact and AWS Config, and automating security processes with AWS Lambda and AWS Systems Manager.
AWS Networking Specialists design the network layer that everything else in an AWS environment depends on, building solutions that are secure, well-performing, and able to support applications used around the world. They focus on minimising latency and maximising bandwidth at global scale, so users get a fast, responsive experience no matter where they're connecting from. Isolation and security are central to their designs, creating network environments where workloads are properly segmented and protected from unauthorised access. They also work on hybrid cloud setups, connecting on-premises data centres to AWS so organisations can extend their existing infrastructure into the cloud without a disruptive all-at-once migration. In practice, this means designing secure, scalable network architectures with Amazon VPC, building global content delivery networks with Amazon CloudFront, ensuring secure, low-latency connections with AWS Direct Connect, and maintaining network security using AWS Security Groups and Network ACLs.
AWS Machine Learning Specialists use AWS's machine learning services to take models from initial idea through to a working, deployed system, moving faster than building everything from scratch. They lean on AWS's data analytics tools to understand the data feeding their models, identifying patterns and issues that need to be addressed before training begins. Once a model is ready, they focus on deploying it in a way that's reliable and able to scale with demand, so it performs consistently in production. Because models can drift or become outdated as data changes, they also build in processes for continuous learning, retraining and refining models over time so they stay accurate. Day to day, this means developing and training machine learning models with Amazon SageMaker, optimising data analysis workflows with AWS Glue and Amazon Athena, deploying models using Amazon SageMaker and AWS Lambda, and implementing continuous improvement processes using AWS's machine learning tools.
AWS IoT Specialists connect fleets of devices, sensors, and equipment to AWS securely and at scale, building the foundation that lets an organisation collect data from the physical world and act on it. They set up the pipelines needed to gather and analyse data streaming in from these devices, turning raw signals into information that's useful for monitoring and decision-making. For applications where timing is critical, they build systems that can process data in real time, enabling fast responses to changing conditions out in the field. They also implement centralised tools for managing and monitoring large numbers of devices, so fleets can be updated, monitored, and troubleshot without visiting each device individually. In practice, this means securely connecting devices with AWS IoT Core, analysing IoT data with AWS IoT Analytics, processing real-time data with AWS IoT Greengrass and AWS Lambda, and centrally managing devices with AWS IoT Device Management.
AWS Database Administrators design and manage database solutions that stay fast and reliable as data volumes and query loads grow, choosing the right AWS database service for each workload's needs. Security and data protection are core responsibilities, with databases configured to keep sensitive information safe and backed up so it can be recovered if something goes wrong. They automate routine management tasks wherever possible, using AWS's database management tools to reduce manual maintenance work and the risk of mistakes. They also support the wider organisation's analytics needs, making sure data stored in databases can feed into reporting and analysis with minimal extra effort. Day to day, this means optimising database management with services like Amazon RDS, Aurora, and DynamoDB, ensuring database security and backups with AWS Backup and AWS Key Management Service, monitoring and optimising performance with tools like Amazon RDS Performance Insights, and improving data analysis processes using Amazon Redshift and other analytics services.
AWS Cloud Consultants help organisations figure out not just how to use AWS, but how to use it well, developing cloud strategies that fit a business's goals, constraints, and existing systems. A recurring focus is cost, helping teams understand where their cloud spend is going and putting practices in place to keep it under control as usage grows. For organisations moving to AWS for the first time, or expanding their use of it, they plan and manage migration and transformation processes so workloads move over smoothly with minimal disruption. They also design custom solutions where off-the-shelf approaches don't quite fit, combining AWS services in ways tailored to specific business needs. In practice, this means developing cloud strategies tailored to your business, optimising costs with AWS Cost Explorer and other cost management tools, managing migrations with AWS Migration Hub and related tools, and developing and integrating custom solutions using a wide range of AWS services.
AWS Application Developers build applications designed to run natively on AWS, taking advantage of managed services so applications can scale without the team needing to manage underlying servers directly. They work with AWS's modern development tooling to write, test, and iterate on code efficiently, keeping development cycles short even as applications grow more complex. A priority throughout is fast, reliable deployment, getting new features and fixes into users' hands quickly without introducing risk. Continuous integration and delivery practices tie all of this together, connecting development and deployment into a single smooth workflow. Day to day, this means developing scalable applications with services like AWS Elastic Beanstalk and AWS Lambda, using tools like AWS Cloud9 to support efficient coding, optimising continuous integration and deployment with AWS CodePipeline and CodeDeploy, and monitoring and improving application performance with AWS X-Ray and CloudWatch.
AWS Support Engineers are the people users turn to when something on AWS isn't working as expected, providing technical support that resolves issues quickly so teams can get back to what they were doing. They keep a close eye on the performance of AWS services in use, watching for warning signs and addressing problems before they become bigger issues. When something does go wrong, they bring strong troubleshooting skills to identify root causes in often complex AWS environments rather than just treating symptoms. Beyond reactive support, they also help users build their own skills, providing training and guidance so teams become more self-sufficient over time. In practice, this means resolving technical issues using the AWS Support Center and other support tools, monitoring and optimising service performance with AWS CloudWatch and related tools, identifying and fixing issues with tools like AWS Trusted Advisor, and educating users through AWS Training and Certification programs.
AWS Data Scientists work with large datasets on AWS to uncover insights that inform business decisions, using AWS's data analytics tools to explore and make sense of data at scale. They develop machine learning models and train them using AWS's infrastructure, taking advantage of managed services rather than maintaining their own training environments. Where data is generated continuously, they build the capability to analyse streams in real time, refining and improving models as new data arrives rather than only at fixed intervals. To make their findings actionable, they also focus on visualisation, presenting data and model outputs in ways that support clear decision-making across the business. Day to day, this means optimising data analysis with tools like Amazon Athena and Redshift, developing and training models with Amazon SageMaker and other machine learning services, analysing data streams in real time with AWS Kinesis, and visualising data using tools like Amazon QuickSight.
AWS Cloud Trainers help teams build genuine competence with AWS, going beyond surface-level familiarity to make sure people can use these services confidently and correctly. They guide users through certification programs, giving teams a recognised way to validate and demonstrate their AWS skills. Because AWS services evolve constantly, trainers stay on top of new releases and changes, making sure the guidance they provide reflects how things actually work today, not how they worked a year ago. Practical, hands-on training is central to their approach, helping people learn by working through realistic scenarios rather than just reading documentation. In practice, this means educating and certifying users through AWS Training and Certification programs, building skills with practical tools like AWS Workshops, keeping training content up to date with the latest AWS services, and supporting continuous development through ongoing training and guidance.