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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - BFSI Cloud & Payments Platform - **Company:** Peoplentech Llc - **Location:** Alexandria, VA, United States - **Experience:** Expert - **Salary:** $135,200 - $145,600 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Batch Processing, Cloud Computing, Cloud Engineering, Data Cleansing, Information Engineering, Data Governance, Data Infrastructure, Data Security, Data Systems, Distributed Computing Environment, Distributed Systems, Fault Tolerance, Graph Database, Intrusion Detection Systems, Python (Programming Language), Log Analysis, Neo4j, Named Entity Recognition, NoSQL, Operational Data Store, Performance Tuning, Systems Development Life Cycle, Cloud Services, Software Engineering, SQL Databases, Transaction Processing (Computing), Data Processing, Apache Spark, Software Troubleshooting, Event Driven Architecture, Build Management, Containerization, Pyspark, Kubernetes, Information Technology, ISO 20022 Standard, Real Time Data, Apache Kafka, Spark Streaming, Data Management, ISO 8583, ArcSight Event Correlation, Stream Processing, Data Pipelines, Devsecops - **Published:** November 7, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-data-engineer-bfsi-cloud-payments-platform-alexandria-va--ce332d26-e86b-4efb-a443-1f09b2d2642d ## About the Role Software Engineering, Cloud Computing, Reconciliation, Financial Services, Data Processing, Cloud Computing, Transaction Processing/Management, Banking Services, Data Management, Scalable System Development, * Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or related field. * 8+ years of experience in Data Engineering and distributed data processing. * Strong hands-on expertise with: + Apache Kafka + Apache Spark/PySpark + Python + SQL + NOSQL DB + CDC Frameworks + Event-Driven Architectures + Graph Databases * Experience building large-scale streaming and batch processing pipelines. * Strong understanding of distributed systems and real-time data processing. * Experience with Operational Data platforms * Knowledge of transaction processing systems, event correlation, and log analytics. * Strong troubleshooting, performance tuning, and optimization skills., * Banking and Financial Services domain experience. * Hands-on experience with Payments and Transaction Processing platforms. * Knowledge of ISO 8583, ACH, RTP, SWIFT, and ISO 20022 standards. * Experience with Neo4j and Graph Database technologies. * Familiarity with Knowledge Graph and Graph Analytics solutions. * Experience supporting observability and transaction monitoring platforms. * Exposure to AI/ML and GenAI-enabled analytics solutions. * Cloud certifications in Azure, AWS, or GCP preferred. ## Description We are seeking an experienced Senior Data Engineer to design, develop, and optimize large-scale real-time data platforms supporting transaction tracing, reconciliation, observability, analytics, and graph-enabled investigations for Banking and Financial Services (BFSI) clients. The role requires expertise in streaming architectures, event-driven systems, distributed data processing, transaction lifecycle management, and modern cloud data platforms., Real-Time Data Engineering & Platform Development * Design and develop real-time and batch data ingestion pipelines. * Build scalable data processing frameworks using Kafka, Spark Streaming, and PySpark. * Develop cloud-native and distributed data processing solutions. * Create reusable data engineering components, frameworks, and accelerators. * Design highly available, fault-tolerant, and performance-optimized data pipelines. * Establish data engineering standards, patterns, and best practices. BFSI Data Processing & Transaction Traceability Develop and support data solutions across: * Payments Platforms (ACH, RTP, FedNow, SWIFT, ISO 20022) * ATM Transaction Processing Key responsibilities include: * Design transaction tracing and correlation frameworks. * Create canonical transaction and event processing models. * Correlate transactions using STAN, RRN, timestamps, terminal IDs, and account references. * Build reconciliation and exception management workflows. * Enable end-to-end transaction lifecycle visibility and auditability. * Perform log analysis and transaction mapping. Data Quality, Reliability & Observability * Implement reconciliation, validation, and data quality frameworks. * Establish end-to-end lineage tracking across all processing stages. * Detect missing transactions, duplicate events, processing anomalies, and broken lineage chains. * Build monitoring, alerting, and operational observability solutions. * Define data quality metrics, SLAs, and operational dashboards. * Support root-cause analysis and transaction recovery investigations. Security, Governance & Compliance * Ensure adherence to banking security and regulatory requirements. * Implement secure data processing and access control mechanisms. * Implement data encryption, masking, and secure data handling practices. * Support audit, lineage, traceability, and regulatory reporting requirements. * Ensure compliance with enterprise data governance standards. Cloud Engineering & DevSecOps * Build and deploy cloud-native data engineering solutions. * Implement CI/CD pipelines for data platform deployments. * Support containerized workloads and Kubernetes-based data platforms. * Enable DevSecOps practices across data engineering solutions. Data, Analytics & Knowledge Graph Engineering * Design Operational Data platform Data pipelines. * Develop real-time analytics and event-streaming pipelines. * Design data preparation and transformation pipelines for Neo4j and graph databases. * Implement entity extraction and relationship mapping frameworks. * Build graph-ready datasets supporting transaction tracing and investigation. * Support graph analytics, impact analysis, and root-cause investigations. * Enable AI/ML and GenAI initiatives through trusted and governed data assets. Leadership & Stakeholder Management * Collaborate with solution architects, business teams, operations, payments, fraud, and technology stakeholders. * Participate in architecture reviews, technical governance, and design discussions. * Mentor junior and mid-level data engineers. * Support estimation, planning, and technical solution discussions., * High-performance real-time data processing pipelines. * Accurate transaction correlation and traceability across systems. * Reliable transaction lineage and audit tracking. * High-quality graph-ready datasets supporting investigations and analytics. * Improved observability and operational monitoring. * Reduced transaction processing failures and reconciliation gaps. * Secure, scalable, and compliant data engineering solutions. * Successful delivery of enterprise-grade data platforms supporting banking and payments modernization.