Remote Data Engineer, Mortgage Servicing

Job Description Note: The job is a remote job and is open to candidates in USA. reputed company is seeking a Data Engineer specializing in Mortgage Servicing. This role is crucial for building and evolving data systems that support analytics, reporting, and AI development, while ensuring data integrity and operational efficiency. Responsibilities Design, build, and maintain robust data pipelines for a wide variety of input and output sources, including internal systems, third-party platforms, files, APIs, event streams, and databasesDevelop scalable ETL and ELT workflows for both batch and real-time processingEnsure pipelines are reliable, testable, observable, and easy to extend as business needs evolveBuild reusable data integration patterns that support growing volumes, new source systems, and downstream consumers across analytics, applications, and AI initiativesDesign and manage data architectures that support OLTP, OLAP, and reporting workloads across operational and analytical environmentsBuild and optimize data models, warehouse schemas, and curated datasets for analytics and BI use casesContribute to the design and operation of modern data platforms, including warehouses, lakehouses, streaming systems, and supporting orchestration frameworksHelp define patterns for data storage, partitioning, performance optimization, retention, and lifecycle managementDesign and maintain data models that accurately reflect loan-level lifecycle events, including payment activity, balances, adjustments, and status changesEnsure consistency and reconciliation across systems where transactional, financial, and reporting data must alignIdentify and resolve discrepancies across source systems, and build data structures that support accurate, auditable outputs for downstream operational processes, reporting, and decisioningDeploy, operate, and improve data pipelines and data stores on major cloud platforms such as AWS, GCP, or AzureUse infrastructure-as-code, CI/CD, and automation practices to improve deployment speed, consistency, and reliabilityMonitor production data systems using logging, alerting, and observability tooling to proactively identify and resolve issuesSupport secure, resilient, and cost-conscious operation of cloud-based data infrastructureImplement data quality checks, validation rules, reconciliation processes, and monitoring to ensure trustworthy data across systemsEstablish and maintain standards for reputed company, documentation, metadata, schema evolution, and operational runbooksPartner with stakeholders to improve data accessibility, consistency, and usability while maintaining appropriate controls and governanceContribute to practices that support security, privacy, auditability, and compliance in a regulated environmentPartner closely with Product, Engineering, and business stakeholders to understand data needs, workflows, and constraintsTranslate business and operational requirements into clean, scalable, and maintainable data solutionsSupport downstream consumers of data, including analysts, researchers, product teams, and operational usersCommunicate clearly with both technical and non-technical stakeholders about data availability, quality, tradeoffs, and delivery timelinesContinuously improve pipeline performance, reliability, scalability, and developer productivityIdentify opportunities to simplify architecture, reduce operational toil, and improve data platform leverage across teamsOperate with a strong bias tow