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Senior BI Engineer

We are looking for a Senior BI Engineer with strong data modeling experience, and owning and rebuilding the manufacturing reporting layer, ensuring accurate, trusted, and automated operational reporting. The ideal candidate will work closely with operations, software engineering, and data engineering teams to validate business metrics, redesign datasets, and deliver scalable QuickSight dashboards.

Key Responsibilities

Strong data modeling experience, including designing fact and dimension schemas from business requirements and creating intuitive data models for business users.Designing the data model. Identify a sensible, simple model (fact and dimension tables) that would yield those dashboardsAssess existing QuickSight dashboards, Athena/Redshift datasets, and reporting workflows.Analyze and resolve data quality and reporting discrepancies.Validate KPIs and business metrics with operations stakeholders.Rebuild and optimize the reporting layer from source tables through dashboards.Develop and automate WBR/MBR dashboards using Amazon QuickSight.Work with AWS data platforms including Athena, Redshift, S3, Glue, and PySpark.Implement reporting logic for calendars, shifts, utilization, throughput, cycle times, on-time delivery, yield, and backlog metrics.Create self-service datasets, templates, and documentation for business users.Support future analytics, data, and automation initiatives.

Required Skills

10 years of experience in BI, Analytics Engineering, or Data Engineering.Experience owning the reporting layer end-to-end, from source data through dashboards.Strong SQL expertise, including complex joins, window functions, and performance tuning.Hands-on experience with Amazon QuickSight (SPICE, calculated fields, row-level security, dashboards).Strong AWS experience with Athena, Redshift, S3, Glue, and PySpark.Python/PySpark experience for data validation, profiling, and transformation.Experience working with operational, manufacturing, supply chain, logistics, or production data.

Preferred Skills

Manufacturing, MES, ERP, or shop-floor analytics experience.Experience supporting WBR/MBR reporting and KPI frameworks.Knowledge of operational metrics such as utilization, throughput, downtime, cycle time, yield, and on-time delivery.

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Hiring Alert!

Role: Junior Electrical Engineer

About the Role

We are seeking curious, hands-on Electrical or Electronics Engineering graduates who enjoy solving real-world technical problems and making physical systems work. This is an excellent opportunity for early-career engineers and technologists who have a strong foundation in electrical systems, some exposure to programming, and a passion for troubleshooting, automation, controls, and hardware integration.

Key Responsibilities

Translate electrical drawings and I/O lists into application configurationsTest configurations in simulation and on real hardware - EtherCAT devices, motorised rollers, sensors, safety I/OSupport commissioning on site as buildings go liveDocument findings, test results, and technical recommendations.Support continuous improvement initiatives and engineering projects.

Required Qualifications

Graduate Degree or Diploma in one of the following: Electrical EngineeringElectrical Engineering TechnologyMechatronics EngineeringElectromechanical EngineeringEquivalent technician or technology programGraduation year between 2022 and 2026

Experience in one or some of the following technologies:PythonMATLABArduino programmingRaspberry Pi projectsLadder Logic / PLC programmingC/C++ or other programming languages

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The Role

This is a hands-on senior engineering role at the platform/middleware layer. The high-level architecture is in place - your job is to build, integrate, and ship against it. You will work in a team that blends avionics, enterprise networking, cloud, and embedded backgrounds, with a dedicated security engineering team supporting the platform. Modern AI-assisted development tooling is used extensively.

What you'll do:

Design and implement core platform modules - cabin network management (VLAN-based traffic segmentation and prioritization across passenger, crew, and airline operational services), connectivity monitoring, and observability. Build and maintain the over-the-air (OTA) software lifecycle pipeline: cryptographically validated updates, staged activation, automatic rollback, and version reporting to ground-side fleet systems. Develop telemetry and health-monitoring infrastructure, including the device-to-cloud data pipeline for fleet monitoring. Integrate software across multiple cabin hardware platforms, maintaining hardware abstraction layers for portability. Build and execute unit, integration, requirements-based, and hardware-in-the-loop tests. Contribute to interface definitions and architecture decision records, and raise the bar through code reviews and design feedback.

What We're Looking For

Required:

6+ years of professional software development experience, with several years leading design or architecture of production systems. Strong Linux-based software development on real devices - C/C++ and/or Python. Solid networking fundamentals: VLANs, routing, QoS / traffic prioritization, and network troubleshooting. Experience with device-to-cloud systems: telemetry, health monitoring, or fleet/device management. Experience building or operating software update pipelines (OTA/firmware: signing, staged rollout, rollback). Containers (Docker; Kubernetes a plus) and modern CI/testing practices. Comfort with ambiguity and autonomy - an early-stage program where strong engineering judgment and clear documentation matter as much as implementation skill.

Nice to have:

Background in in-flight connectivity, satellite communications, avionics, or other safety-adjacent embedded domains. Familiarity with DO-178C software lifecycle (certification itself not required) or avionics interfaces such as ARINC 429. Security engineering exposure: cryptography, secure boot, threat modeling, identity and access controls. Experience with carrier-grade CPE/gateway software (e.g., RDK, OpenWrt, prpl) - this maps directly to the work.

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About the Role
We are seeking multiple talented Android and iOS Engineers to join a growing Connected Living engineering organisation responsible for developing the next generation of Smart Home and Home Security experiences.
Working within cross-functional feature teams, you will help build and enhance mobile experiences across iOS and Android, working closely with backend engineers, product managers, designers and other technology teams. You will contribute to products spanning smart home, connected devices, cameras, security and intelligent home experiences.
This is an exciting opportunity to join a team undergoing significant growth as it expands its Smart Home portfolio and develops new capabilities across both US and UK markets.
Key Responsibilities
Design, develop and maintain high-quality native iOS and/or Android applications for large-scale consumer products.
Work within cross-functional engineering teams focused on specific product and feature areas, including camera onboarding, activation and connected-home experiences.
Collaborate closely with iOS and Android engineers to deliver a consistent experience across mobile platforms.
Integrate mobile applications with backend services, APIs and connected devices.
Develop experiences involving smart-home devices, cameras, sensors and IoT technologies.
Troubleshoot complex technical issues and contribute to improving application performance, reliability and scalability.
Work closely with product, UX, QA and backend engineering teams throughout the development lifecycle.
Contribute to engineering best practices, code quality, testing and continuous improvement.
Android Engineers
Strong candidates will have experience with:
Kotlin
Android SDK / Android development
Modern Android development frameworks and architecture
RESTful APIs and backend integration
Bluetooth / BLE
MQTT
Connected devices / IoT
Matter and/or Zigbee
Device provisioning and integration
Localization, internationalisation and externalisation
Consumer-facing mobile applications
Experience working within Smart Home, Connected Home, IoT or device ecosystems is highly desirable.
iOS Engineers
Strong candidates will have experience with:
Swift
Native iOS development
iOS SDK / Xcode
SwiftUI and/or UIKit
Mobile application architecture
RESTful APIs and backend integration
Camera and video experiences
AVFoundation
HLS and/or WebRTC
Bluetooth / connected devices
Consumer-facing mobile applications
Engineers with experience in Kotlin Multiplatform are also encouraged to apply.
What We're Looking For
We're particularly interested in engineers who can combine strong mobile engineering fundamentals with experience building real-world consumer, connected-device or IoT products.
Ideal candidates will demonstrate:
Strong software engineering fundamentals
Commercial experience developing native iOS or Android applications
Experience working within large, complex engineering organisations
Strong understanding of mobile architecture and development best practices
Experience integrating applications with APIs and connected devices
Excellent communication and cross-functional collaboration skills
A problem-solving mindset and ownership of the products they build
Experience with Smart Home, Home Security, IoT, cameras, video streaming or connected devices would be a significant advantage.

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Fiber Analyst

Location: Remote
Contract: 12+ Months

Overview

We are seeking an experienced Fiber Engineer to support fiber network testing, troubleshooting, and remediation activities across ISP and OSP environments. This role will focus on OTDR analysis, fiber characterization, bidirectional testing, and documenting findings to ensure network performance and reliability.

Required Qualifications5+ years of experience in Fiber Optics or TelecommunicationsExperience with ISP and OSP fiber networksStrong expertise with OTDR testing and troubleshootingExperience performing CD/PMD, bidirectional, and power meter/laser testingKnowledge of fusion splicing, fiber repair, and remediationExperience with fiber end-face inspection and cleaningProficiency with Microsoft Word and ExcelStrong communication, documentation, and problem-solving skillsAbility to travel as required for field workKey ResponsibilitiesPerform OTDR testing to validate fiber paths and identify faults, splices, bends, and signal lossConduct fiber characterization, bidirectional testing, and power/loss analysisTroubleshoot fiber network issues and recommend remediation solutionsPerform fusion splicing and fiber repairs as neededPrepare test reports, redlined fiber documentation, and demarcation mapsCoordinate with vendors, project managers, and internal teams to support project executionTravel to customer sites for testing, troubleshooting, and remediation activitiesWhat You'll OwnFiber testing and validationOTDR analysis and troubleshootingRemediation and fusion splicing activitiesTechnical reporting and documentationVendor and stakeholder communicationFiber network performance verificationDeliverablesOTDR, CD/PMD, and power/loss test reportsRedlined fiber path documentation and demarcation mapsDocumented remediation and retest resultsTest findings and recommendations shared with vendors and project stakeholders

Required: Prior experience in Fiber Testing, OTDR Analysis, ISP/OSP Networks, Fiber Characterization, and Telecommunications environments.

GCS is acting as an Employment Business in relation to this vacancy.

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GCS is acting as an Employment Business in relation to this vacancy.

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Software Developer - IoT / Edge Computing

Job Summary
We are looking for a Software Developer to join the team on a contract basis and help build a data pipeline supporting an IoT-based quality control device. This role will focus on developing software that connects edge devices to the cloud, enabling reliable data ingestion, processing, and analysis.

The ideal candidate will have strong Python development experience, hands-on experience with AWS IoT services, and a background working with data pipelines that move information from physical hardware/edge devices into cloud environments. Experience developing machine learning models, particularly anomaly detection, is a strong plus.

Key Responsibilities

Develop and maintain software supporting an IoT quality control device.Build and optimize data ingestion pipelines from hardware/edge devices to the cloud.Develop Python applications running on NVIDIA Jetson edge devices.Integrate IoT devices with AWS using technologies such as MQTT, AWS Lambda, and Amazon S3.Design reliable workflows for collecting, transmitting, processing, and storing device-generated data.Collaborate with engineering teams to troubleshoot and improve device-to-cloud connectivity and data flows.Support the development and implementation of data-driven quality control solutions.Potentially develop or integrate machine learning models for anomaly detection to identify unusual device or production behavior.

Required Qualifications

Experience developing software with Python.Hands-on experience with AWS IoT and cloud-based data workflows.Experience with MQTT and IoT device communication.Experience working with AWS Lambda and S3.Experience developing software for edge devices, preferably NVIDIA Jetson.Experience designing data ingestion pipelines from hardware to cloud.Strong understanding of cloud-based data processing and storage.

Preferred Qualifications

Experience building machine learning models.Experience with anomaly detection or predictive analytics.Experience working with IoT, industrial technology, manufacturing, or quality-control systems.Experience deploying ML/software solutions to edge devices.

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Job Description:

A big enterprise customer in fullfillment center is seeking an experienced Technical Program Manager (TPM) or Senior Technical Program Manager (Sr. TPM) to lead execution of large-scale fiber deployment programs within the Global Connectivity Infrastructure Delivery - Fiber Deployment (GCID-FD) organization.

GCID-FD delivers the physical fiber infrastructure that connects AWS data centers globally, including underground conduit systems, fiber cable installation, splicing, testing, commissioning, and infrastructure handoff. This role is responsible for driving fiber capacity into service across the Americas, managing complex infrastructure programs from early site assessment through construction closeout and operational handoff.

The successful candidate will own cross-functional program execution, vendor management, quality control initiatives, risk mitigation, stakeholder communication, and delivery of critical network infrastructure supporting AWS's global operations.

Key Responsibilities

Lead end-to-end delivery of fiber deployment programs from planning through construction completion and handoff.Build and manage complex infrastructure programs, defining milestones, schedules, dependencies, and critical paths.Drive execution across multiple vendors, contractors, engineering teams, and stakeholders.Establish and maintain a standardized Quality Control (QC) framework, including pre-construction and post-construction inspections.Develop and manage vendor performance measurement programs using quality and delivery KPIs.Create and implement defect tracking, corrective action, and root cause analysis processes.Ensure infrastructure projects are delivered safely, on schedule, within scope, and to quality standards.Identify program risks, develop mitigation strategies, and proactively resolve execution challenges.Deliver consistent reporting, metrics, and executive-level program updates to GCID-FD leadership and stakeholders.Coordinate project closeout activities and ensure successful operational handoff of deployed infrastructure.

Required Qualifications

Experience managing large-scale physical infrastructure deployment programs.Proven ability to lead projects involving planning, vendor coordination, field execution, quality control, and project handoff.Demonstrated success building programs from the ground up, including:Defining project structures and governanceEstablishing milestones and schedulesIdentifying critical path dependenciesManaging risks and resolving execution challengesStrong vendor and contractor management experience.Track record of delivering complex programs through execution, not just planning.Excellent stakeholder management and communication skills.

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Machine Learning Engineer

Position Overview

We are looking for a Machine Learning Engineer I with strong Python programming skills to develop, deploy, and optimize machine learning solutions for ad monetization and personalization. You'll collaborate with cross-functional teams to build scalable ML pipelines, enhance recommendation and targeting models, and deliver production-ready AI solutions that improve user engagement and business outcomes.

Key Responsibilities

Develop, train, and deploy machine learning models for personalization, recommendation, and customer experience applications.Build and maintain scalable data pipelines for feature engineering, model training, validation, and inference.Collaborate with machine learning scientists, data engineers, and software engineers to transition research models into production.Enhance recommendation and ranking models using customer behavioural and transactional data.Monitor, evaluate, and improve model performance through experimentation, A/B testing, and data-driven analysis.Write clean, efficient, and maintainable Python code following software engineering best practices.Optimize machine learning workflows to improve customer engagement and support business objectives.Participate in model deployment, monitoring, troubleshooting, and continuous improvement initiatives.Document machine learning processes, model performance, and technical solutions to support collaboration and knowledge sharing.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, or a related field.1-3 years of experience in machine learning, including internships, research, or professional experience.Strong programming skills in Python.Solid understanding of machine learning concepts, including supervised learning, feature engineering, model evaluation, classification, and regression.Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.Experience working with SQL and large datasets.Familiarity with Git and software development best practices.

What You'll Learn

Build and deploy production-ready machine learning models at scale.Gain hands-on experience with recommendation systems, personalization, and ranking algorithms.Learn best practices for feature engineering, model monitoring, and performance optimization.Work with large-scale data processing and modern machine learning pipelines.Develop expertise in experimentation frameworks, A/B testing, and data-driven decision-making.Collaborate with experienced machine learning engineers, software engineers, and data scientists on real-world AI solutions.Strengthen your understanding of MLOps concepts, including model deployment, versioning, and lifecycle management.Improve your software engineering skills by contributing to scalable, maintainable, and production-quality codebases.

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