Data Integration and Machine Learning Engineer
Fatima Group · Lahore, Punjab, Pakistan
Tailor my CV for this job — freePurpose:This role is critical for the success of our AI initiatives. The value of AI/ML solutions depends on the quality and availability of enterprise data, sound problem formulation, and reliable model training. The Data Integration and Machine Learning Engineer will ensure data from various systems is accurate, complete, and usable; integrate data with internal and external systems; and develop production-ready ML solutions that deliver measurable business value.
Key Responsibilities
Design and implement AI solutions integrated with ERP, cloud, ECM, IoT, and DCS systemsBuild and maintain APIs and data pipelines for reliable AI and ML adoptionPrepare enterprise data for AI agents using RAG, embeddings, and vector databasesEmbed security by design across data integration, AI, and ML activitiesEstablish scalable data mesh architecture with metadata, lineage, and documentationPartner with IT and business teams to define ML problems, baselines, metrics, and validationDevelop and deploy ML models for forecasting, optimization, and other business use casesApply statistics and feature engineering with leakage-free validation and explainabilityExperience Required:3 to 5 years in data engineering, ML, or integration roles, ideally within manufacturing or ERP-driven industriesStrong hands-on experience with ERP, cloud, ECM, or similar enterprise applications and production data pipelinesEnd-to-end experience developing, deploying, and monitoring ML solutionsExperience with forecasting, optimization, or recommendation systems is an advantageTechnical Skills (Preferred):Languages & Tools: SQL, Python, PL/SQL, Apache Airflow, Talend, REST APIsML & Statistics: scikit-learn, pandas, XGBoost or similar; regression, classification, clustering, time-series forecasting, anomaly detection, model evaluation, optimization using OR-Tools, Pyomo, or similar;Systems & Databases: Oracle, PostgreSQL, AWS/Azure Data Lake, NoSQLData Management: Data cataloging, validation frameworks, observability tools