Experience:

5 years required

Skills:

Oracle, ERP

Job type:

Full-time

• Lead the integration architecture between Oracle Retail applications, Oracle Fusion Cloud, and other source systems using Oracle GoldenGate-based integration, APIs, file-based interfaces, middleware, and database-level integration where applicable.
• Ensure that business transactions from Oracle Retail and other applications are accurately captured, transformed, validated, and recorded in Oracle Fusion for financial and operational processing.
• Lead and develop a team of ERP and integration application developers responsible fo ...
• Collaborate with business stakeholders from Finance, Retail Operations, Procurement, Supply Chain, IT, and other departments to gather requirements and translate them into technical solutions, integrations, reports, and support processes.
• Work closely with Oracle Fusion functional teams, Oracle Retail teams, database administrators, infrastructure teams, and external implementation/support partners to deliver stable and scalable solutions.
• Ensure effective integration between Oracle SaaS applications, Oracle Retail applications, on-premise systems, cloud platforms, data platforms, and third-party applications.
• Define and enforce integration standards, data validation rules, error handling mechanisms, reconciliation controls, retry processes, and audit trails for transaction recording into Oracle Fusion.
• Provide technical leadership for incident resolution, root cause analysis, service requests, production issues, and performance problems related to Oracle Fusion, Oracle Retail integrations, GoldenGate replication, and connected applications.
• Ensure compliance with enterprise IT standards, security policies, data governance requirements, audit controls, and regulatory expectations.
• Identify opportunities to improve integration reliability, automation, monitoring, performance, scalability, and maintainability.
• Support project execution, system testing, cutover planning, migration activities, production deployment, hypercare, and post-go-live stabilization.
• Ensure proper documentation of technical designs, integration flows, data mappings, operational procedures, support runbooks, and knowledge transfer materials.
• Build internal capability so that the Makro / CP AXTRA application team can enhance, maintain, monitor, and support the Oracle Fusion integration landscape after project handover.
• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Minimum of 5 years of experience in ERP implementation, integration, or production support for enterprise ERP platforms such as Oracle Fusion Cloud, Oracle E-Business Suite, SAP, or similar systems.
• Strong experience with Oracle Fusion Cloud applications, especially in finance-related modules such as General Ledger, Payables, Receivables, Fixed Assets, Procurement, or related ERP processes.
• Experience with Oracle Retail applications, retail transaction systems, merchandising systems, inventory systems, or store/back-office integration is highly desirable.
• Hands-on experience or strong working knowledge of Oracle GoldenGate, data replication, CDC-based integration, transaction synchronization, and reconciliation processes.
• Experience integrating Oracle Fusion with upstream and downstream systems using APIs, FBDI, BI Publisher reports, Oracle Integration Cloud, database procedures, flat files, middleware, or other integration technologies.
• Familiarity with Oracle Autonomous Database, Oracle Database, PL/SQL, Oracle APEX, Oracle Integration Cloud, Oracle Data Integrator, Microsoft SQL Server, Java,.NET, shell scripting, or Python is preferred.
• Strong understanding of finance transaction recording, accounting interfaces, period-end processing, reconciliation, error handling, and audit requirements.
• Knowledge of ERP and retail business processes, including procurement, inventory, sales, supplier invoices, payments, financial accounting, and management reporting.
• Demonstrated leadership experience in managing technical teams, vendors, and cross-functional project stakeholders.
• Experience in retail, wholesale, FMCG, or large enterprise environments is advantageous.
• Strong analytical and problem-solving skills, with the ability to investigate complex integration, data, and application issues.
• Good understanding of IT controls, application security, data governance, change management, and production support practices.
• Effective communication skills, both verbal and written, with the ability to explain technical topics clearly to business users, management, vendors, and technical teams.
• Preferred Experience.
• Oracle Fusion Cloud ERP implementation or support experience.
• Oracle Retail integration experience.
• Oracle GoldenGate implementation or operational support experience.
• Experience supporting high-volume transaction interfaces from retail systems into ERP.
• Experience with transaction monitoring, automated reconciliation, exception handling, and batch/interface support.
• Experience working with finance, procurement, supply chain, and retail operations teams.
• Experience managing system cutover, migration, production deployment, and hypercare activities.

Experience:

6 years required

Skills:

Cloud Computing, Architecture, Postgre SQL, Automation, Leadership Skill

Job type:

Full-time

• AI & Advanced Analytics Enablement.
• Lead the design, development, and deployment of enterprise AI, Machine Learning, and Generative AI solutions to support business transformation (e.g., pricing, promotion, automation, recommendation, demand forecasting, customer insights, and intelligent decision support).
• Build and manage scalable data pipelines supporting AI/ML model training, inference, feature engineering, Feature Store, RAG knowledge bases, and LLM applications.
• Develop reusable datasets, AI-ready data products, feature engineering pipelines, and semantic data models for AI Engineers, Data Scientists, and Business Analytics teams.
• Partner closely with AI Engineers to design, deploy, productionize, and scale AI/ML models, LLM applications, Agentic AI, AI Chatbots, Recommendation Systems, and Mobile AI applications.
• Design and maintain data ingestion pipelines for structured, semi-structured, and unstructured data from enterprise systems, APIs, databases, files, event streams, IoT devices, and third-party platforms.
• Develop scalable data pipelines supporting document ingestion, embedding generation, metadata management, vector indexing, and retrieval workflows for RAG applications.
• Identify opportunities to embed AI into business workflows and operational decision-making to improve efficiency, customer experience, and business value.
• Data Platform & Engineering Leadership.
• Own end-to-end enterprise data architecture from source systems to Data Lake, Lakehouse, Data Warehouse, Feature Store, Semantic Layer, and AI-serving layers.
• Design, develop, and optimize scalable ETL/ELT pipelines supporting batch, micro-batch, streaming, and near real-time data processing.
• Design and maintain workflow orchestration for enterprise data pipelines using Databricks Workflows, Apache Airflow, or equivalent orchestration frameworks.
• Develop enterprise-scale Big Data solutions using Apache Spark and distributed computing frameworks.
• Design scalable logical and physical data models while optimizing database architecture for performance, scalability, reliability, and cost efficiency.
• Ensure enterprise data quality, governance, lineage, metadata management, observability, security, and compliance across data platforms.
• Implement automated data validation, monitoring, logging, alerting, and observability to ensure production-grade data reliability.
• Optimize SQL queries, Spark workloads, partitioning strategies, storage formats, and compute resources for maximum performance and cost efficiency.
• Analyze complex technical issues, identify root causes, troubleshoot production problems, and recommend infrastructure and platform improvements.
• Select, evaluate, and integrate modern data engineering tools, cloud technologies, and AI platform frameworks to support evolving business needs.
• Continuously evaluate emerging technologies in Big Data, Lakehouse Architecture, Data Platform Engineering, Cloud Computing, and AI Platform Engineering.
• AI Platform & Infrastructure.
• Build and maintain enterprise AI data infrastructure supporting LLM, RAG, Agentic AI, AI Chatbots, Recommendation Engines, Intelligent Search, and Intelligent Automation platforms.
• Design and implement scalable AI data pipelines supporting batch, streaming, vector search, embedding pipelines, and Retrieval-Augmented Generation (RAG) architectures.
• Design scalable APIs, data services, and integration layers connecting AI applications with enterprise systems and digital platforms.
• Collaborate with AI Engineers to prepare high-quality datasets for LLM fine-tuning, prompt engineering, model evaluation, inference, and continuous model improvement.
• Support deployment and operationalization of AI products using DataOps, MLOps, CI/CD, containerization, and modern software engineering practices.
• Drive continuous improvements in platform scalability, availability, security, observability, resilience, and operational efficiency.
• Team Leadership & Capability Building.
• Lead, mentor, and develop a high-performing team of Data Engineers, AI Engineers, and Analytics professionals.
• Foster engineering excellence through best practices in architecture design, coding standards, testing, code reviews, deployment, technical documentation, and software engineering.
• Drive architecture reviews, technical design reviews, engineering governance, and platform standardization across the engineering organization.
• Define engineering standards, technical roadmaps, platform architecture, and technology strategy aligned with business objectives.
• Collaborate closely with Product Owners, Business Stakeholders, AI Engineers, Data Scientists, Solution Architects, Infrastructure, and DevOps teams.
• Provide hands-on technical leadership with a strong engineering mindset and willingness to troubleshoot complex production systems.
• Promote continuous learning, knowledge sharing, innovation, and adoption of emerging technologies across the engineering team.
• Bachelor's degree or higher in Computer Science, Computer Engineering, Information Technology, Artificial Intelligence, Data Engineering, Management Information Systems, or a related field.
• 6+ years of experience in Data Platform Engineering, Data Engineering, Big Data, or AI Platform development, with experience leading engineering teams.
• Strong experience designing and implementing enterprise-scale Data Lake, Lakehouse, Data Warehouse, or Modern Data Platform architectures.
• Expert proficiency in SQL, Databricks SQL, PostgreSQL, database design, and query performance optimization.
• Strong programming skills in Python.
• Hands-on experience with Apache Spark, Databricks, Delta Lake, Spark SQL, Unity Catalog, and distributed data processing.
• Strong experience designing and developing scalable ETL/ELT pipelines and workflow orchestration.
• Experience with streaming technologies such as Spark Structured Streaming, Kafka, or equivalent.
• Experience building enterprise-scale data platforms supporting AI/ML, Advanced Analytics, and Generative AI applications.