Qureos Mentor

Datamatics Technologies

<div>
 
 
 Position:
 
 iOS Developer / Engineer
 
 
 Contract Type:
 
 Short-Term DMT Contract (3&ndash;6 Months)
 
 
 Location:
 
 Offshore
 
 
 Experience Level:
 
 Mid&ndash;Senior (5-7 Years)
 
 
 
 Role Overview
 
 
 We are looking for an experienced
 
 iOS Developer / Engineer
 
 to design, build, and maintain high-quality mobile applications for iPhone and iPad. The ideal candidate should be proficient in Swift 6, modern concurrency, SwiftUI, and advanced iOS frameworks to deliver seamless, user-friendly applications.
 
 
 
 Key Responsibilities
 
 <ul>
 <li>
 
 Design and develop iOS applications using
 
 Swift 6
 
 with structured concurrency.
 
 </li>
 <li>
 
 Build responsive interfaces using
 
 SwiftUI
 
 (with UIKit as secondary knowledge).
 
 </li>
 <li>
 
 Implement efficient data management using
 
 SwiftData
 
 .
 
 </li>
 <li>
 
 Develop modular and scalable application architecture using
 
 The Composable Architecture (TCA)
 
 .
 
 </li>
 <li>
 
 Create interactive features like
 
 Live Activities
 
 and
 
 Dynamic Island
 
 integrations.
 
 </li>
 <li>
 
 Implement
 
 App Intents &amp; Shortcuts
 
 for enhanced user automation support.
 
 </li>
 <li>
 
 Work with
 
 Xcode Cloud
 
 and
 
 Fastlane
 
 for CI/CD automation.
 
 </li>
 <li>
 
 Collaborate with designers, QA, and backend teams to ensure end-to-end delivery.
 
 
 </li>
 </ul>
 
 Key Expertise Required
 
 <ul>
 <li>
 
 Swift 6 + structured concurrency
 
 </li>
 <li>
 
 SwiftUI (UIKit secondary skill)
 
 </li>
 <li>
 
 SwiftData (Core Data replacement)
 
 </li>
 <li>
 
 The Composable Architecture (TCA)
 
 </li>
 <li>
 
 Live Activities &amp; Dynamic Island
 
 </li>
 <li>
 
 App Intents &amp; Shortcuts integration
 
 </li>
 <li>
 
 Xcode Cloud + Fastlane automation
 
 
 </li>
 </ul>
 
 Preferred Skills
 
 <ul>
 <li>
 
 Experience publishing apps to the App Store
 
 </li>
 <li>
 
 Strong debugging and performance optimization skills
 
 </li>
 <li>
 
 Familiarity with REST APIs, JSON, and modern iOS design patterns
 
 </li>
 </ul>
</div>

iOS Developer

<div>
 
 Job Title: Enterprise Data Architect
 
 
 
 Location:
 
 &nbsp;Remote with Travel (MEA Region)
 
 
 Experience:
 
 10+ Years
 
 
 Certification:
 
 TOGAF Certified (Mandatory)
 
 
 Employment Type:
 
 Full-Time
 
 
 Job Summary
 
 
 We are seeking a highly skilled and experienced
 
 Enterprise Data Architect
 
 with strong expertise in designing and implementing large-scale enterprise solutions. The ideal candidate must be
 
 TOGAF Certified
 
 and possess a minimum of 10 years of experience in enterprise and data architecture. This role involves defining data strategies, developing architecture blueprints, and ensuring alignment between IT initiatives and organizational business goals. The individual will also be responsible for optimizing data assets, establishing governance frameworks, and supporting presales activities.
 
 
 
 Key Responsibilities
 
 
 Enterprise &amp; Solution Architecture
 
 <ul>
 <li>
 
 Develop, maintain, and communicate comprehensive enterprise architecture models aligned with business objectives, IT strategy, and industry best practices.
 
 </li>
 <li>
 
 Engage with business and technology stakeholders to understand requirements and design scalable, future-ready architectural solutions.
 
 </li>
 <li>
 
 Lead the creation of data architecture blueprints, roadmaps, and implementation plans for enterprise-wide initiatives.
 
 </li>
 <li>
 
 Conduct architecture assessments to identify gaps, risks, and improvement opportunities and propose actionable recommendations.
 
 </li>
 </ul>
 
 Data Architecture &amp; Data Management
 
 <ul>
 <li>
 
 Design, implement, and maintain conceptual, logical, and physical data models supporting business and analytical needs.
 
 </li>
 <li>
 
 Define data standards, naming conventions, classification policies, and metadata frameworks to ensure data integrity and consistency.
 
 </li>
 <li>
 
 Develop end-to-end data integration strategies across diverse systems and platforms.
 
 </li>
 <li>
 
 Establish and enforce data governance frameworks to support data quality, security, compliance, and lifecycle management.
 
 </li>
 <li>
 
 Implement data profiling, cleansing, cataloging, and metadata processes to uphold data accuracy and reliability.
 
 </li>
 </ul>
 
 Database Systems &amp; Optimization
 
 <ul>
 <li>
 
 Evaluate and select appropriate database and storage technologies based on scalability, performance, and cost considerations.
 
 </li>
 <li>
 
 Design and optimize database schemas, indexes, and queries for efficient data storage, access, and performance.
 
 </li>
 <li>
 
 Provide leadership and oversight in database architecture decisions across the enterprise.
 
 </li>
 </ul>
 
 Leadership &amp; Cross-Functional Collaboration
 
 <ul>
 <li>
 
 Provide technical leadership, mentoring, and guidance to cross-functional teams, ensuring adherence to architectural standards.
 
 </li>
 <li>
 
 Support presales activities including proposals, RFPs, SOW creation, and collateral development.
 
 </li>
 <li>
 
 Foster a culture of continuous improvement and knowledge sharing across technical and non-technical teams.
 
 </li>
 <li>
 
 Stay updated on emerging technologies, trends, and best practices to continuously enhance the enterprise architecture landscape.
 
 </li>
 </ul>
 
 Travel Requirement
 
 <ul>
 <li>
 
 Willingness and readiness to travel to client locations within the
 
 MEA region
 
 for medium to long-term assignments.
 
 
 </li>
 </ul>
 
 Qualifications
 
 <ul>
 <li>
 
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Technology, or a related field.
 
 </li>
 <li>
 
 
 TOGAF Certification is mandatory.
 
 
 </li>
 <li>
 
 Minimum of
 
 10 years&rsquo; experience
 
 designing and implementing enterprise and data architecture solutions in complex, large-scale environments.
 
 </li>
 <li>
 
 Strong expertise with architecture modeling tools (e.g., ArchiMate, TOGAF Architect) and enterprise architecture platforms.
 
 </li>
 <li>
 
 Proficiency in data modeling tools such as
 
 ERwin, ER/Studio
 
 , and strong knowledge of database systems (Oracle, SQL Server, MySQL, etc.).
 
 </li>
 <li>
 
 Experience with
 
 data warehousing, data lakes, big data platforms
 
 , and modern data architectures.
 
 </li>
 <li>
 
 Familiarity with
 
 cloud data platforms
 
 (AWS, Azure, GCP) and DevOps methodologies.
 
 </li>
 <li>
 
 Excellent analytical, problem-solving, and decision-making abilities.
 
 </li>
 <li>
 
 Strong communication and interpersonal skills, with the ability to engage stakeholders across all levels of the organization.
 
 </li>
 </ul>
</div>

Enterprise Data Architect

<div>
 
 
 Job Description: Data Scientist (MLOps, CI/CD, Generative AI)&nbsp;
 
 Experience : 4 to 6 Years
 
 Location: Isb / Hybrid
 
 
 
 About the Role&nbsp;
 
 
 We are seeking a Full Stack Data Scientist with strong expertise in MLOps, CI/CD, and Generative AI to join our growing AI/ML team. This role is highly dynamic and requires a balance of technical excellence, customer-facing skills, and business acumen.&nbsp;
 
 
 You will be responsible for the end-to-end machine learning lifecycle&mdash;from data exploration and model development to deployment and optimization. A key part of the role is engaging with customers, understanding their business challenges, and delivering impactful Proof of Concepts (POCs) that build trust and demonstrate value.&nbsp;
 
 
 Candidates with hands-on expertise in statistical models, traditional ML, deep learning architectures, time series forecasting, and financial modeling will be strongly preferred.&nbsp;
 
 
 Experience with GPUs, CUDA, and high-performance computing is a plus, given the scale and complexity of deep learning and Generative AI workloads.&nbsp;
 
 
 Key Responsibilities&nbsp;
 
 <ul>
 <li>
 
 Engage directly with customers to understand business problems and translate them into data science solutions.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Design and deliver impactful projects that clearly demonstrate value and help win new business opportunities.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Build and deploy end-to-end ML/AI solutions across domains such as NLP, Computer Vision, Generative AI, and Forecasting.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Develop and optimize MLOps pipelines for model training, deployment, and monitoring with CI/CD best practices.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Implement statistical, traditional ML, and deep learning models, ensuring accuracy, scalability, and robustness.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Create time series and financial forecasting models for predictive analytics in business and finance use cases.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Apply Generative AI methods (LLMs, RAG, LangChain, Hugging Face, Diffusion Models) to enterprise use cases.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Optimize training and inference with GPU acceleration and CUDA where applicable.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Ensure production-grade deployment with monitoring, drift detection, and retraining strategies.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Collaborate with product managers, engineers, and stakeholders to align technical solutions with business outcomes.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Stay updated with industry trends and bring innovative AI/ML solutions to customer engagements.&nbsp;
 
 </li>
 </ul>
 
 Required Qualifications&nbsp;
 
 <ul>
 <li>
 
 Education: Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, AI/ML, or related field.&nbsp;
 
 </li>
 </ul>
 
 
 <ul>
 <li>
 
 Experience: 3+ years of professional experience in end-to-end ML/AI solution delivery.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Technical Expertise:&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Statistical models (hypothesis testing, regression, time series analysis).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Traditional ML (SVM, decision trees, ensemble methods, clustering, recommendation systems).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Deep Learning (CNNs, RNNs, LSTMs/GRUs, Transformers, GANs, Diffusion Models).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Time Series &amp; Financial Models (ARIMA, Prophet, advanced LSTM/GRU models, risk prediction).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Generative AI (LLMs, RAG, LangChain, Hugging Face Transformers, OpenAI APIs).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proficiency in Python (NumPy, Pandas, Scikit-learn, Statsmodels, TensorFlow, PyTorch).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Hands-on experience with MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Strong knowledge of CI/CD workflows (GitHub Actions, GitLab CI, Jenkins, Azure DevOps).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience with cloud platforms (AWS, Azure, GCP) for ML deployment and scaling.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Strong understanding of Docker, Kubernetes, and production deployment.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Excellent communication and presentation skills to face customers confidently.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proven ability to translate customer requirements into POCs and production solutions..&nbsp;
 
 </li>
 </ul>
 
 Preferred/Bonus Skills&nbsp;
 
 <ul>
 <li>
 
 Experience with GPUs, CUDA, and high-performance model training.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Familiarity with real-time inference frameworks (TensorRT, Triton, TorchServe, FastAPI).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Knowledge of feature stores (Feast, Tecton) and monitoring tools (Evidently, WhyLabs, Prometheus, Grafana).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Exposure to financial services, supply chain, or enterprise AI domains.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Track record of winning client trust through successful POCs and solution delivery.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Contributions to open-source ML/AI projects.&nbsp;
 
 </li>
 </ul>
</div>

Data Scientist

<div>
 
 
 
 
 
 The Role: Data Governance Functional Lead/Sr. Manager
 
 
 
 
 
 
 
 Location: Remote (Pak) / Hybrid (Riyadh, KSA)
 
 
 
 Employment Type: Full-Time / Contract-to-Hire
 
 
 
 Experience Level: 8+ years
 
 
 
 
 
 
 
 
 Job Description:
 
 
 &nbsp;
 
 
 
 
 
 
 
 
 Reporting to the Director of the organization, the Data Governance Functional Lead/Sr. Manager at Datamatics Technologies will be instrumental in supporting and executing data governance initiatives across the organization. The Senior Data Governance Consultant is responsible for providing strategic and functional expertise in data management, data governance, data privacy and security&nbsp; to the organization/clients. This role involves working closely with clients to understand their data management needs, designing and implementing data governance frameworks, processes, policies and procedures related to data governance, data security and data lifecycle.
 
 
 
 
 
 
 
 
 
 
 
 Responsibilities:&nbsp;
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 Collaborate with clients, business, technology teams to understand their data management and governance needs and translate them into technical solutions and project objectives.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Collaborate with clients and within Datamatics Technologies to align their business and technology priorities
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Interaction with senior management at a client and Datamatics Technologies to steer recommendations and obtain buy-in on matters that may require alternate approach
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Lead the Data Governance project teams to implement consistent data governance standards and technology solutions across the organization/at the client.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Assist in creating and managing an inventory of business and product datasets and their interdependencies.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Develop and deliver training to staff on using data effectively and data governance practices, data privacy, data security; to ensure data governance policies and practices are embedded throughout the organisation
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Support business development efforts by participating in client presentations and proposal development
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Develop and enforce KPIs related to data governance and data security to accurately monitor the effectives of the data governance programme.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Define Data Governance roles, responsibilities, accountability, and ownership and decision rights.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Drive organizational change management and the use of data, data governance, privacy frameworks, processes realizing vision of data managed as an asset
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Strong client-facing skills and the ability to build and maintain effective relationships with clients.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Willingness to travel Internationally (KSA, MEA region) to client sites as needed to lead the projects/assignment.
 
 
 
 
 
 
 </li>
 </ul>
 
 
 
 
 Develop planning activities, documentation and policies for:
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 Data Governance maturity assessment (
 
 
 define the current state, future state and target state
 
 
 )
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Data Governance, Data Security, Data Operations frameworks and Operating models
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Data Architecture and Data Modelling
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Data Quality, Metadata &amp; Classification
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Data Storage Forecasting
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Tools and Technology Evaluation
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Data Integration Plan and Target DI Architecture
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Master and Reference Data Management
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Data Value Realization Plan
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Data Value Realization Use Cases
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Open Data
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Data Sharing
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Data Privacy, Data Security and Data Protection
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Compliance Monitoring and Audit, Health Checks
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 SLAs
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Configuration Management
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Trainings
 
 
 
 
 
 
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 
 
 
 
 
 
 
 
 
 Must have
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 Bachelors or Masters in Computer Science, MIS, or Information Management
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Minimum of 10 years of experience in a major organization, leading the large-scale data projects and oversight experience.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 5+ years working in a Data Governance lead role.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 3+ years of experience in data quality management, metadata, cataloguing.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 4+ years in data warehousing, business intelligence, analytical solutions implementation.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Knowledge of data governance practices, processes, methodologies, business and technology issues related to management of enterprise information assets and approaches related to data protection (e.g. DAMA)
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Demonstrates strong problem solving capabilities
 
 
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 
 
 
 
 Prioritization and sense of urgency to meet commitments
 
 
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 
 
 
 
 Self-starter, ability to adapt and quickly develop in-depth technical understanding of new/different applications. Understanding of Data Warehouse and Data Marts concepts, ETL best practices.
 
 
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 
 
 
 
 Data Management/Governance Tools Knowledge: Familiarity with industry-standard data governance tools such as business glossary, metadata management, data quality, master and reference data, data catalog, ETL and business intelligence tools
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Excellent communication skills, with the ability to effectively communicate technical concepts to clients and team members to non-technical executives in both written and verbal channels
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Builds good relationships with peers, executives and other departments
 
 
 
 
 
 
 </li>
 </ul>
 
 
 
 
 &nbsp;
 
 Good To have:
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 Implementation experience in data governance tools solutions. e.g.
 
 
 Collibra, Erwin, Informatica (DQ, AXON, EDC, MDM) etc.
 
 
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 
 
 
 
 Data privacy, data security, principles, and regulations (e.g., GDPR, ISO 270001 etc.).
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Certification in Data Governance and Data Management recognized in the industry e.g. CDMP
 
 
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 
 
 
 
 Experience in implementing the NDMO Framework will be a great plus.
 
 
 
 
 
 </li>
 </ul>
</div>

Data Governance Functional Lead/Sr. Manager

<div>
 
 
 
 
 Job Title: Confluent Kafka Infrastructure Administrator
 
 
 
 
 
 
 
 
 
 Location: Remote (Pak) / Hybrid (Riyadh, KSA)
 
 
 
 
 
 
 
 
 
 Employment Type: Full-Time / Contract-to-Hire
 
 
 
 
 
 
 
 
 
 Experience Level: 5+ years
 
 
 
 
 
 
 
 
 
 
 Role Summary
 
 
 
 
 
 
 
 
 
 As a
 
 Confluent Kafka Infrastructure Administrator
 
 , you'll be the operational backbone for our Kafka ecosystem, handling the full lifecycle of clusters from installation to ongoing maintenance. You'll deploy and manage Confluent Platform in multi-environment setups (dev/test/UAT/preprod/prod/DR), ensuring high availability, security, and performance. This hands-on role involves automation, troubleshooting, and collaboration with engineering teams to support real-time data pipelines in production-scale environments.
 
 
 
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 Installation &amp; Setup:
 
 Lead the deployment and initial configuration of Confluent Platform (Enterprise/Cloud editions) and Apache Kafka clusters across multiple environments (dev, test, UAT, preprod/prod, DR), including:
 
 
 
 
 <ul>
 <li>
 
 
 
 
 Installing brokers, ZooKeeper/KRaft controllers, Schema Registry, Kafka Connect, and ksqlDB using automated tools like Ansible, Terraform, or Confluent CLI/Helm charts on Kubernetes, bare-metal, or cloud (GCP).
 
 
 
 
 </li>
 <li>
 
 
 
 
 Configuring topics, partitions, replication factors, and security (SSL/TLS encryption, SASL authentication, ACLs/RBAC via ZooKeeper or KRaft) with zero-downtime setups.
 
 
 
 
 </li>
 <li>
 
 
 
 
 Integrating auxiliary services like MirrorMaker 2 or Confluent Replicator for cross-environment replication, and performing initial load testing/health checks with tools like Kafka's perf tools.
 
 
 
 
 </li>
 <li>
 
 
 
 
 Automating environment provisioning for reproducibility, including VPC peering, load balancers, and integration with existing infrastructure.
 
 
 
 
 </li>
 </ul>
 </li>
 <li>
 
 
 
 
 
 Maintenance &amp; Operations:
 
 Oversee day-to-day cluster management, upgrades, and patching in multi-environment landscapes, ensuring &gt;99.9% uptime and compliance with SLAs.
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Monitoring &amp; Troubleshooting:
 
 Implement and maintain observability with Prometheus, Grafana, Confluent Control Center; set up alerts for metrics like lag, throughput, and broker health; perform root-cause analysis for incidents (e.g., replication failures, disk exhaustion).
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Optimization &amp; Scaling:
 
 Conduct capacity planning, performance tuning (e.g., JVM tweaks, partition balancing), and horizontal/vertical scaling; implement Tiered Storage for cost efficiency in large-scale setups.
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Security &amp; Compliance:
 
 Enforce security best practices (OAuth/Kerberos, auditing); manage access controls and ensure GDPR/HIPAA compliance across environments.
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Automation &amp; Documentation:
 
 Develop scripts (Python/Bash) for routine tasks like backups, rollouts, and failover; create runbooks and contribute to IaC pipelines (CI/CD with Jenkins/GitHub Actions).
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 Collaboration:
 
 Partner with data engineers, DevOps, and architects to support POCs, integrations (e.g., Flink/Spark), and environment migrations; provide 24/7 on-call support for prod incidents.
 
 
 
 
 
 </li>
 </ul>
 
 
 
 
 Required Qualifications &amp; Skills
 
 
 
 
 <ul>
 <li>
 
 
 
 Bachelor's in Computer Science/Engineering; Confluent Certified Administrator (CCAAK) or equivalent a plus.
 
 
 
 </li>
 <li>
 
 
 
 5+ years in infrastructure ops; 3+ years hands-on with Confluent Platform &amp; Apache Kafka (KRaft mode preferred).
 
 
 
 </li>
 <li>
 
 
 
 Proven track record in deploying/managing Kafka clusters across multi-environments (dev/test/UAT/preprd/prod/DR); expertise in Ansible/Terraform/Helm for automated installs.
 
 
 
 </li>
 <li>
 
 
 
 Proficiency in Bash/Python scripting; Kafka admin APIs, Connect, Streams, ksqlDB; Confluent CLI, REST Proxy.
 
 
 
 </li>
 <li>
 
 
 
 Containerization (Docker/K8s); CI/CD (Jenkins/GitHub Actions); multi-cloud (AWS/GCP/Azure) with managed services like MSK.
 
 
 
 </li>
 <li>
 
 
 
 Tools like Prometheus/Grafana/ELK; experience with upgrades, backups, DR (MirrorMaker/Replicator), and performance tuning.
 
 
 
 </li>
 <li>
 
 
 
 SSL/TLS, SASL, ACLs/RBAC; auditing and compliance in distributed systems.
 
 
 
 </li>
 <li>
 
 
 
 Strong troubleshooting, documentation, and communication; ability to handle on-call rotation.
 
 
 
 </li>
 </ul>
</div>

Confluent Kafka Infrastructure Administrator

<div>
 
 Job Title:
 
 AI Data Scientist (Offshore)
 
 
 
 Duration:
 
 6 Months (Extendable)
 
 
 Experience:
 
 &nbsp;6&ndash;8 Years
 
 
 Location:
 
 Offshore (Remote)
 
 
 Industry:
 
 Multi-Industry (with focus on Financial Sector)
 
 
 Employment Type:
 
 Contract (6 Months - Higher possiblity for extension)
 
 
 
 Job Summary
 
 
 We are seeking a highly skilled
 
 AI Data Scientist
 
 with hands-on experience in building and deploying advanced data science and machine learning models, particularly within the
 
 financial services domain
 
 . The ideal candidate will have strong proficiency in
 
 Python, SQL
 
 , and
 
 Google Cloud Platform (GCP)
 
 tools &mdash; leveraging platforms like
 
 BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, GCS, and Looker
 
 to deliver scalable and automated AI solutions.
 
 
 This is an exciting
 
 6-month contract role (with potential extension)
 
 focused on developing
 
 descriptive, predictive, and prescriptive models
 
 and deploying them in production using
 
 MLOps best practices
 
 .
 
 
 
 Key Responsibilities
 
 <ul>
 <li>
 
 Design and develop
 
 data science and machine learning models
 
 across descriptive, predictive, and prescriptive analytics.
 
 </li>
 <li>
 
 Work closely with business stakeholders&mdash;especially in the
 
 financial sector
 
 &mdash;to translate complex problems into AI-driven solutions.
 
 </li>
 <li>
 
 Develop and automate
 
 end-to-end ML pipelines
 
 on
 
 GCP
 
 using Vertex AI, Dataflow, Pub/Sub, and Dataproc.
 
 </li>
 <li>
 
 Implement
 
 MLOps
 
 frameworks for continuous integration, deployment, and monitoring of machine learning models.
 
 </li>
 <li>
 
 Analyze large datasets using
 
 BigQuery
 
 and other GCP-native tools for data transformation, feature engineering, and model training.
 
 </li>
 <li>
 
 Visualize insights and performance metrics using
 
 Looker
 
 and other BI tools.
 
 </li>
 <li>
 
 Collaborate with data engineers, analysts, and cloud architects to ensure seamless model deployment and scalability.
 
 </li>
 <li>
 
 Evaluate model performance and refine algorithms for improved accuracy and business impact.
 
 
 </li>
 </ul>
 
 Required Skills &amp; Qualifications
 
 <ul>
 <li>
 
 
 5&ndash;8 years
 
 of professional experience in
 
 data science, AI/ML
 
 , and analytics roles.
 
 </li>
 <li>
 
 Proven expertise in
 
 Python
 
 (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and
 
 SQL
 
 for data analysis and model development.
 
 </li>
 <li>
 
 Hands-on experience with
 
 GCP ecosystem
 
 , including:
 
 <ul>
 <li>
 
 
 BigQuery
 
 (data querying and transformation)
 
 </li>
 <li>
 
 
 Vertex AI
 
 (model training, tuning, deployment)
 
 </li>
 <li>
 
 
 Dataflow / Dataproc
 
 (data processing pipelines)
 
 </li>
 <li>
 
 
 Pub/Sub
 
 (event-driven data streaming)
 
 </li>
 <li>
 
 
 GCS (Google Cloud Storage)
 
 and
 
 Looker
 
 (visualization and reporting)
 
 </li>
 </ul>
 </li>
 <li>
 
 Strong knowledge of
 
 MLOps automation
 
 and continuous deployment best practices.
 
 </li>
 <li>
 
 Experience developing models in
 
 financial services
 
 (risk scoring, fraud detection, customer analytics, forecasting, etc.).
 
 </li>
 <li>
 
 Strong understanding of
 
 statistical modeling
 
 ,
 
 feature engineering
 
 , and
 
 model performance evaluation
 
 .
 
 </li>
 <li>
 
 Excellent problem-solving and communication skills with ability to work in multi-industry environments.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 
 Experience in
 
 multi-cloud
 
 or hybrid environments.
 
 </li>
 <li>
 
 Knowledge of
 
 CI/CD pipelines
 
 for ML (GitHub Actions, Jenkins, or Cloud Build).
 
 </li>
 <li>
 
 Exposure to
 
 deep learning frameworks
 
 (TensorFlow, PyTorch).
 
 </li>
 <li>
 
 Experience in
 
 time-series forecasting
 
 ,
 
 credit modeling
 
 , or
 
 financial risk analytics
 
 .
 
 </li>
 </ul>
</div>

AI Data Scientist

Join Datamatics Technologies and explore 10   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Datamatics Technologies

ABOUT_COMPANY

iOS Developer

Enterprise Data Architect

Data Scientist

Data Governance Functional Lead/Sr. Manager

Confluent Kafka Infrastructure Administrator

AI Data Scientist

AI Data Scientist