Cloud Security Engineer Jobs

Machine Learning Engineer We’re looking for a Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: Multiple years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native:

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

About THG Ingenuity THG Ingenuity is a fully integrated digital commerce ecosystem, designed to power brands without limits. Our global end-to-end tech platform is comprised of three products: THG Commerce, THG Studios, THG Fulfilment. Each represents a single, unified solution, overcoming challenges and taking brands direct-to-consumer. Our client portfolio includes globally recognised brands such as Coca-Cola, Nestle, Elemis, Homebase, and Proctor & Gamble. Database Platform Manager Company: THG Ingenuity Location: Manchester (Head Office) Reports to: Director of Data Role Overview We are looking for a strong technical leader to run our database platform. Our estate runs on Google Cloud Platform following a recent migration to self-managed services, and there is a real opportunity here to shape the next phase. How we consolidate and modernise the estate, where managed and cloud-native services earn their place, which new technologies are worth adopting, and how the platform scales with the business are all live questions. You will lead the thinking on them and work with stakeholders across the business to agree and deliver the roadmap. You will lead our DBA team, who own every database across the group regardless of the application running on it and who run the platform as a 24/7 service. You will work hand in hand with our Data Reliability Engineering team, whose Principal Engineer is your peer and whose focus is automation, fleet reliability and SLOs. This role is weighted toward hands-on technical depth. You should be as credible in a design review or an incident bridge as you are in a planning session with senior stakeholders. Key Responsibilities Technical direction The technical roadmap for the estate. We want someone genuinely interested in emerging database technologies who evaluates them on merit and can articulate the pros and c

About THG Ingenuity THG Ingenuity is a fully integrated digital commerce ecosystem, designed to power brands without limits. Our global end-to-end tech platform is comprised of three products: THG Commerce, THG Studios, THG Fulfilment. Each represents a single, unified solution, overcoming challenges and taking brands direct-to-consumer. Our client portfolio includes globally recognised brands such as Coca-Cola, Nestle, Elemis, Homebase, and Proctor & Gamble. The Role We are seeking a talented and commercially astute Data Scientist to join our dynamic team tackling Fraud, Payments and Finance. In this multi-focus role, you will be responsible for protecting our global e-commerce operations from fraud, optimising our payments performance and driving profitability and automation initiatives within Finance. Working with vast, complex datasets, the work will involve combatting online fraud using our award-winning THG Detect platform and driving payments optimisation by increasing authorisation rates, while also using the latest AI software and Google Cloud Platform (GCP) infrastructure to build complex data solutions and applications. This role requires a blend of strong technical skills, commercial acumen, and effective communication to translate complex data insights into tangible business value. Responsibilities: Optimise Fraud Detection: Continuously improve automated decision-making in our in-house THG Detect platform using machine learning and decision rules. Enhance Payment Performance: Lead data-driven initiatives to boost payment authorisation rates, optimise transaction routing, and reduce costs. Drive Profitability within Finance: Lead automation and profitability initiatives across different areas of Finance. Communicate Performance: Report on all aspects of fraud, payments and finance performance to stakeholders at all levels, including C-level management. Drive System Improvements: Collaborate with Fraud, Payments, F

Who Are We HALA is a leading fintech player in the MENAP region that aims to redefine financial services and build the future bank of SMEs. HALA aims at empowering SMEs to start, run, and grow their businesses by providing them with cutting-edge financial and technological tools. HALA currently holds multiple entities in UAE, Saudi Arabia and Egypt (including HALA Payments and HALA Logistics) and offers solutions that enable merchants to digitize their payments as well as manage their sales and operations. Founded in 2017, HALA is currently licensed by the Saudi Arabian Central Bank. Objective We are seeking IT Audit Manager to join our team and lead audits across Information Technology, Cybersecurity, Business Continuity Management (BCM), and other technology-enabled business processes. The Senior IT Auditor will be responsible for planning and executing risk-based audits, evaluating the design and operating effectiveness of IT general controls (ITGCs), cybersecurity controls, technology governance, cloud environments, business continuity and disaster recovery capabilities, and regulatory compliance. The role also involves identifying technology risks and control deficiencies, assessing their impact on the organization, and providing practical recommendations to strengthen governance, enhance cyber resilience, improve operational effectiveness, and support compliance with applicable regulatory requirements and industry standards. Responsibilities Plan and execute risk-based IT audit engagements, including IT General Controls (ITGC), cybersecurity, cloud computing, digital platforms, data governance, business continuity management (BCM), disaster recovery (DR), third-party risk, and technology-enabled business processes. Perform audit planning activities, including risk assessments, audit scoping, control identification, and development of audit programs and testing procedures. Evaluate the design and operating effectiveness of IT controls, identify technolog

Required Skills: Core Java: Strong understanding of Java SE, including OOP concepts, data structures, and algorithms. Frameworks: Experience with popular Java frameworks such as Spring and Hibernate. Web Technologies: Knowledge of web technologies including JSP, Servlets, HTML, CSS, and JavaScript. Database Management: Proficiency in working with relational databases like MySQL, PostgreSQL, or Oracle, including SQL queries and optimization. Version Control: Experience with version control systems like Git, including branching, merging, and pull requests. Build Tools: Familiarity with build tools like Maven or Gradle. RESTful Services: Ability to design and consume RESTful web services and APIs. Testing: Experience with unit testing frameworks like JUnit or TestNG. Problem-Solving: Strong analytical and problem-solving skills with the ability to troubleshoot and resolve complex issues. Preferred Skills: Spring Boot: Experience with Spring Boot for creating microservices. ORM: Proficiency with Object-Relational Mapping (ORM) tools like Hibernate or JPA. Frontend Technologies: Basic knowledge of frontend frameworks like Angular, React, or Vue.js. Cloud Platforms: Experience with cloud platforms such as AWS, Azure, or Google Cloud. Continuous Integration/Deployment (CI/CD): Familiarity with CI/CD tools such as Jenkins or GitLab CI. Microservices Architecture: Understanding of microservices architecture and containerization with Docker. Qualifications: Education: Bachelor’s degree in Computer Science, Information Technology, or a related field. Experience: 2-4 years of professional experience in Java development. Personal Attributes: Team Player: Ability to work collaboratively in a team environment. Communication: Strong verbal and written communication skills. Attention to Detail: High attention to detail and a commitment to delivering high-quality software. Adaptability: Ability to adapt to new technologies and changing requirements.

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. What we are looking for? Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services ( MS Azure, GCP preferred) , ML Modeling, Spark & Kafka. Proven problem-solving skills and a solution-oriented mindset. Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Candidates with similar skill sets and experiences have excelled in technology firms or consultancy firms. Successful ca

About the Role We are looking for a Senior SAP BW/BI Developer to design, build, and optimize enterprise data warehousing solutions on SAP BW. The ideal candidate has deep hands-on experience across the full SAP BW/BI stack — from data extraction and ABAP development to performance tuning and cross-platform data integration — and can independently own complex data solutions from design through production support. Key Responsibilities Design and develop SAP BW/BI solutions, including data models, extraction logic, and reporting objects to support business analytics needs. Build and maintain data ingestion pipelines from SAP ECC and functional modules including PM, FI/CO, SD, MM, and C4C into SAP BW. Develop, enhance, and debug custom extractors, user exits, and enhancements using ABAP programming. Design and build DSOs (Data Store Objects), InfoCubes, and BEx Queries to support reporting and analytics requirements. Develop and maintain APDs (Analysis Process Designer) to extract data from BW and push output files to application servers for downstream consumption. Analyze, troubleshoot, and optimize BW query and load performance, particularly for large data volumes. Build and support connectivity between SAP BW and external data platforms, preferably Cloudera and/or Google Cloud Platform (GCP). Design, schedule, and monitor Process Chains to automate data loads and ensure data availability SLAs are met. Manage Transport Requests across development, quality, and production landscapes following change management best practices. Create and maintain technical documentation, including design specs, data flow diagrams, and process runbooks. Collaborate with functional consultants, business analysts, and downstream data teams to translate business requirements into technical solutions. Provide production support, root-cause analysis, and long-term fixes for data and performance issues Requ

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. What we are looking for? 2-5 years: Data Engineer Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka. Proven problem-solving skills and a solution-oriented mindset. Experience working with business stakeholders either internally or externally Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Minimum of a bachelor's

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. What we are looking for? 2-5 years: Data Engineer Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka. Proven problem-solving skills and a solution-oriented mindset. Experience working with business stakeholders either internally or externally Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Minimum of a bachelor's

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Scientist, your primary role revolves around leveraging Python and SQL to conduct data science modelling, employing statistical and machine learning algorithms to derive actionable insights. Your responsibilities will encompass: Data Modeling: Developing and implementing sophisticated data science models to extract valuable insights from complex datasets. Algorithm Implementation: Applying statistical and machine learning algorithms to solve business problems and enhance decision-making processes. Visualization: Utilizing visualization tools like Tableau and PowerBI to present findings in a compelling and understandable manner. Cloud-Based Deployment: Deploying models on cloud platforms such as MS Azure, GCP, and AWS, optimizing their functionality and scalability. What we are looking for? Proficiency in Python, SQL, data science modeling, and statistical analysis. Strong grasp of ML algorithms and their implementation in real-world scenarios. Experience in visualization tools like Tableau and PowerBI, along with knowledge of deploying models on cloud platforms (MS Azure, GCP, AWS). Proven problem-solving skills and a solution-oriented mindset. Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Candidates with similar skill sets and experiences have e

Level Up Your Career with Zynga! At Zynga, we bring people together through the power of play. As a global leader in interactive entertainment and a proud label of Take-Two Interactive, our games have been downloaded over 6 billion times—connecting players in 175+ countries through fun, strategy, and a little friendly competition. From thrilling casino spins to epic strategy battles, mind-bending puzzles, and social word challenges, our diverse game portfolio has something for everyone. Fan-favorites and latest hits include FarmVille™, Words With Friends™, Zynga Poker™, Game of Thrones Slots Casino™, Wizard of Oz Slots™, Hit it Rich! Slots™, Wonka Slots™, Top Eleven™, Toon Blast™, Empires & Puzzles™, Merge Dragons!™, CSR Racing™, Harry Potter: Puzzles & Spells™, Match Factory™, and Color Block Jam™—plus many more! Founded in 2007 and headquartered in California, our teams span North America, Europe, and Asia, working together to craft unforgettable gaming experiences. Whether you're spinning, strategizing, matching, or competing, Zynga is where fun meets innovation—and where you can take your career to the next level. Join us and be part of the play! Position Overview: The Senior Director, Data Platform will lead Zynga's centralized data platform and product strategy, managing one of the largest data footprints in the gaming industry—billions of daily gameplay events flowing through a cloud-native stack spanning real-time ingestion, a petabyte-scale warehouse, experimentation, and a self-serve metrics and AI platform. Operating with high autonomy and direct executive sponsorship, you will act as a pathfinder: empowering our global studios to extract maximum value from central data and transforming the group to an AI-first way of working. This highly visible role is based in Toronto and partners closely with studio leaders, central teams, and executives across Zynga's global labels. Relocation support is available. What You'll Do: Craft data product strategy:

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. We’re looking for a curious, driven professional to join our Revenue Analytics team. This builds and owns the data products, reporting infrastructure, semantic foundations, and analytical systems that power Affirm’s Revenue organization. As a Analyst at Revenue Analytics, you’ll build scalable data products that power day-to-day decision-making - owning end-to-end work across data modeling, metric definitions, dashboards, automation, and enablement. You’ll also help strengthen our semantic layer and data governance, laying the foundation for reliable AI. The ideal candidate combines strong technical and analytical skills with the ability to turn ambiguous business questions into durable, well-tested data infrastructure. What you'll do Develop dbt data models, dashboards, metrics, and automation processes for the revenue field team and revenue analysts Build and maintain critical reporting data models that power external merchant reporting Build the semantic, metadata, and context layers that allow AI systems to accurately understand Revenue data, metrics, and business definitions Partner with Business Systems, engineering, and business stakeholders to translate requirements into durable, well-tested data products Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows) Develop processes, governance, and foundations to scale the impact of analytics within Revenue. What we look for 3+ years of work experience in an analytics engineering or business intelligence role Strong working knowledge of SQL, dbt, Python, data modeling, and data visualization Hands-on experience with BI tools (Sigma/Looker/Tableau), Databricks, and cloud data warehouses (Snowflake) Understanding of the data founda

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. We’re looking for a curious, driven professional to join our Revenue Analytics team. This builds and owns the data products, reporting infrastructure, semantic foundations, and analytical systems that power Affirm’s Revenue organization. As a Senior Analyst, Revenue Analytics, you’ll build scalable data products that power day-to-day decision-making - owning end-to-end work across data modeling, metric definitions, dashboards, automation, and enablement. You’ll also help strengthen our semantic layer and data governance, laying the foundation for reliable AI. The ideal candidate combines strong technical and analytical skills with the ability to turn ambiguous business questions into durable, well-tested data infrastructure. What you'll do Develop dbt data models, dashboards, metrics, and automation processes for the revenue field team and revenue analysts Build and maintain critical reporting data models that power external merchant reporting Build the semantic, metadata, and context layers that allow AI systems to accurately understand Revenue data, metrics, and business definitions Partner with Business Systems, engineering, and business stakeholders to translate requirements into durable, well-tested data products Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows) Develop processes, governance, and foundations to scale the impact of analytics within Revenue. What we look for 3+ years of work experience in an analytics engineering or business intelligence role Strong working knowledge of SQL, dbt, Python, data modeling, and data visualization Hands-on experience with BI tools (Sigma/Looker/Tableau), Databricks, and cloud data warehouses (Snowflake) Understanding of the data f

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the VP of Data & Revenue Engineering, this is a high visibility role with the opportunity to work on greenfield projects. If you’re a data engineer with a builder mindset who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat! What You Will Be Doing Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma ( Tech we use : Fivetran, dagster, dlt, terraform, dbt, Snowflake, Sigma, Hightouch, Metaplane) Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses Scale our terraform deployment across all of our Snowflake assets Continue to advance our data governance policies Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levels Qualifications We Need Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks) Strong communication and collaboration skills. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success. Experience deploying data governance frameworks with a scalable and repeatable process Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that 3+ years of relevant experience wor