Mohammad Adil

▪ AI-Driven Banking Innovation: Led the design and delivery of fintech platforms integrated with Open Banking,
leveraging FastAPI, Azure Data Engineering pipelines, and Apache Kafka for scalable, real-time, and secure digital
banking solutions.
▪ Advanced AI & Voice Transformation: Deployed AI models using PyTorch, TensorFlow, and Hugging Face Transformers
to enable seamless voice recognition, NLP, and transformation technologies for next-gen banking experiences.
▪ Data & Compliance Leadership: Designed AI solutions that adhere to strict financial regulatory requirements, while
delivering actionable insights through Power BI dashboards for performance monitoring and executive decision-making.
▪ Predictive Analytics: Delivered predictive analytics models ensuring operational efficiency today and preparing systems
for future advancements in AI.
▪ Agile Delivery: Spearheaded projects using Agile (Scrum) methodologies, with Jira and Confluence for transparent,
collaborative, and efficient delivery.
Technologies:
▪ Data Science & AI: Machine Learning, NLP, Voice Transformation, Predictive Analytics
▪ Engineering & Development: Python, GoLang, Node.js, Angular, React, Microsoft Stack (C#, ASP.Net Core, MVC, .NET
Standard/Core)
▪ Data Engineering: Azure Data Factory, Azure Data Pipelines, Apache Kafka, TimescaleDB
▪ Solution Architecture: Cloud-Native Infrastructure, API Development, Open Banking Integration, CI/CD
▪ Project Leadership: Agile Delivery, Leading Development Teams, Global/Remote Collaboration

performance and executive decision-making.
• Data Architecture Leadership: Designed and led the implementation of enterprise data architecture, ensuring scalability,
security, and seamless integration with existing systems. Integration experience with external systems/APIs Performance tuning examples or SQL optimization
• Working with global teams or remote setups Data Entities, Extensions, Event Handlers, Batch Jobs
• In a recent smart building project, I helped a client identify that predicting asset degradation for HVAC units was
more impactful than anomaly detection alone.
• Use Azure Arc to deploy to on-prem Kubernetes
• Automated real-time telemetry data collection from various smart devices (LoRaWAN gateways, Modbus sensors,
energy meters) and pushed clean, structured data into TimescaleDB and cloud data lakes.
• Designed workflows to monitor building energy usage and automatically notify teams of abnormal patterns using email,
Slack, and Teams integrations via Orchestrator triggers.
• Developed alert escalation bots that consume telemetry-based thresholds (CO2, temperature, occupancy) and push
priority issues to incident management systems (Jira, ServiceNow).
• Enabled seamless integration with APIs from AWS IoT Core, Azure Hub, and building access control systems, reducing
manual interventions by 85%.
• Collaborated with IoT engineers and DevOps teams to align automation strategies with operational SLAs and real-time
response needs.Technologies: Architecture & Modeling: Entity-relationship modeling, metadata Python, MS
• Digital transformation projects as a Solution Architect and Data Engineer in large-scale and petroleum
enterprises Oman, optimizing production systems, predictive maintenance, and real-time data insights.
• Designed and deployed AI-driven solutions for predictive equipment maintenance, asset optimization, and
operational efficiency in oil production.
• hybrid cloud strategy combining on-prem SCADA systems with Azure-based AI and analytics pipelines.
• Built secure data ingestion and processing frameworks for real-time sensor data from field assets using Azure IoT
Hub, TimescaleDB, and Azure ML.
• Architected event-driven data platforms for subsurface and production analytics using microservices and Azure
Functions.
• Committed to building secure, scalable, and responsible AI solutions, with emphasis on data governance,
GDPR/PII compliance, and stakeholder collaboration—capable of translating complex technical strategies into
measurable business outcomes.

Digital transformation projects as a Solution Architect and Data Engineer in large-scale energy and petroleum
enterprises in Oman, optimizing production systems, predictive maintenance, and real-time data insights.
 Designed and deployed AI-driven solutions for predictive equipment maintenance, asset optimization, and
operational efficiency in oil production.
 hybrid cloud strategy combining on-prem SCADA systems with Azure-based AI and analytics pipelines.
 Built secure data ingestion and processing frameworks for real-time sensor data from field assets using Azure IoT
Hub, TimescaleDB, and Azure ML.
 Architected event-driven data platforms for subsurface and production analytics using microservices and Azure
Functions.
 Committed to building secure, scalable, and responsible AI solutions, with emphasis on data governance,
GDPR/PII compliance, and stakeholder collaboration—capable of translating complex technical strategies into
measurable business outcomes.
Technologies:
▪ Azure ML, OpenAI, Databricks, Data Lakes Azure Synaptics, Cognitive Services, Python, .NET, , TOGAF, SAP GUI Automation,
Excel Macros, ARIBA, JSRS, Regex, API/Webhooks, MS Power Automate (basic), SQL, Python (basic), OCR engines
(Tesseract/Abbyy), Jira, Confluence

• Provide smart buildings solutions to major real estate-, construction- and insurance companies, leading projects around
environmental monitoring, Smart Billing, Smart Grid sensor devices on the IoT- industry. Broad full-stack experience ranging
from Front-End, Services, and Data Layer
• design and delivery of NetCracker-based BSS solutions including Product Catalog, CPQ, Billing, and Customer Care
modules for telecom clients. AL/ML, Telecom Integrator, OSS, Core Network, BSS, VAS
• experience with RESTful APIs, API gateways, Kafka/RabbitMQ, service buses, and microservice orchestration using
Docker and Kubernetes.
• Collaborated with cross-functional teams to map client requirements with eTOM/SID/TAM frameworks ensuring
seamless digital transformations.
• Development of custom delivery solutions of telemetry messages from MQTT to client server (Azure, AWS, IBM Watson and
google cloud)
• Extensively involved in gathering business requirements and system requirements and developing creative solution to meet
business requirements.
• Took responsibility as software architect to understand the requirements in detail the complex requirements for developing
different financial tools and the customer-advisor coordination portal.
• Build system requirement documentation design documents and vulnerable of system
• Implemented Restful web services for client and server-side communication.
• development using .NET, Python, Node Js React, REST API, SOAP, MQ, TCP, and file transfer protocols, XML, fixed length, and
CSV Golan Grafana Dockers PostgreSQL Replication
• Implantation of Opensorce IOT Solutions Fiware and LoraWAN using secured Protocol letsencrypt, OpenVPN and KomBridge.
Technologies:
• LoRaWAN, , TOGAF, NodeJS, Apache Kafka
◦ Data Analysis
◦ Industrial Internet of Things (IIoT)
◦ PyTorch
◦ C#
◦ .NET
◦ Agile
Methodologies
• Software Project Management
◦ Solution Architecture
◦ Databases
◦ PostgreSQL
◦ Python (Programming Language)
◦ Go

CDMP API to support
customer journey analytics and omni-channel marketing automation, aligning with business objectives for
personalized customer engagement. Collaborated with senior leadership to prioritize high-value data initiatives,
fostering a data-driven culture across marketing and product teams.
• Data Platform Design: Architected scalable data ingestion pipelines using Apache Kafka, RabbitMQ, and
D·engages API, integrating structured and semi-structured data from diverse sources into cloud-based data
lakes. Optimized platform performance, reducing data processing latency by 20% and ensuring reliability for
real-time analytics.
• Business Intelligence: Led the design of real-time and historical dashboards using Tableau and Power BI,
powered by D·engages Content Personalization Engine (CPE), to track KPIs, conversion funnels, and campaign
performance. Delivered actionable insights, improving campaign ROI by 18%.
• Data Governance: Established data governance frameworks, leveraging D·engages ISO 27001-compliant
platform to ensure GDPR compliance and audit readiness. Managed sensitive customer data with profile
management and permission history features, maintaining 100% regulatory compliance.
• Advanced Analytics: Developed predictive models for customer segmentation using Python, Azure ML, and
D·engages Automation Hub, enabling automated, trigger-based personalization. Enhanced customer
engagement rates by 15% through AI-driven campaign optimization.
• Stakeholder Engagement: Partnered with cross-functional teams to translate business challenges into scalable
data solutions, integrating D·engage with third-party CRMs and marketing tools. Represented data initiatives in
leadership forums, driving 25% higher adoption of data-driven strategies.
• Continuous Improvement: Championed process optimization by monitoring data workflows with D·engages
analytics and deliverability tracking, reducing data processing errors by 30% through iterative pipeline
enhancements.
Technologies: Python, Apache Kafka, RabbitMQ, Tableau, , TOGAF, Power BI, SQL, Azure ML, D·engage CDMP
API, REST APIs, Data Lakes, Automation Hub, Content Personalization Engine.

Requirement engineering on the basis of client communication
• Responsible to build system requirement documentation design documents and vulnerable of system
• Development On PHP PostgreSQL Shell scripting and system configuration
• Perform daily activity tasks that include cron jobs management and manage
Technologies:
• C++, Boost Framework, C #, , TOGAF, PostgreSQL9.2, CSS-3, PHP, CentOS 6, Shell scripting, Python

• MAXIMO IBM tivoli asset management for IT 7.1 Develop basic components of a multiple-site and multiple-organization
environment
• Mobilink Warehouse Process Automation Warehouse process
• V-Secur™ - Asset Management System will be phased out in two phases. Integration with Current In place Systems Asset
Management IP Development Integration will cover integration with following application interfaces ProQuest IBM Maximo
PetroHive