AI Data Engineer (3–5 Years Experience) – Banking & Payments

We are looking for a skilled AI Data Engineer to join our team and play a key role in building and maintaining scalable data platforms and AI-ready pipelines within banking and payments systems.⚙️ Key ResponsibilitiesBuild and maintain data pipelines (batch, micro-batch, real-time) for banking and payments dataDevelop AI-ready datasets for ML use cases (fraud detection, credit scoring, AML/KYC)Implement data ingestion frameworks from multiple sources (core banking, APIs, payment gateways)Design and manage data storage solutions (Data Lake / Lakehouse / SQL & NoSQL)Ensure data quality, consistency, and validation across workflowsSupport feature engineering and ML pipelinesImplement streaming solutions (Kafka / Event Hub) for real-time processingOptimize performance for handling large-scale transactional datasetsEnsure compliance with data security and regulations (PCI DSS, GDPR)Contribute to CI/CD pipelines and DevOps practices🛠️ Required Skills✅ Core:Strong experience in Python & SQLHands-on experience with Spark / Databricks✅ Data Engineering Tools:Azure Data Factory (ADF)Airflow / DBT / SSIS✅ Streaming:Kafka / Event Hub✅ Cloud:Azure (preferred)AWS / GCP✅ Knowledge:Data modeling (OLTP / OLAP)AI/ML data preparation pipelinesHandling structured & unstructured data🏦 Domain Expertise (Must Have)Experience in Banking / Fintech / Financial ServicesStrong understanding of:Payment flowsTransaction processingISO 20022 / SWIFT / Card systemsExposure to:Fraud DetectionAML / KYC datasets🎓 QualificationsBachelor’s in Computer Science / Data Engineering or related field3–5 years of experience in Data EngineeringBanking experience is highly preferred⭐ Nice to HaveDelta Lake / Lakehouse architectureReal-time analytics / event-driven systemsDocker / Kubernetes / DevOpsData governance tools