[Remote] Data Engineer, Mortgage Servicing

Note: The job is a remote job and is reputed company 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 reputed company and operational efficiency.

Responsibilities

• Design, build, and maintain robust data pipelines for a wide reputed company of input and reputed company sources, including internal systems, reputed company-party platforms, files, reputed company, event streams, and databases
• reputed company reputed company ETL and ELT workflows for both batch and reputed company-time processing
• Ensure pipelines are reliable, testable, observable, and easy to reputed company as business needs reputed company
• Build reusable data integration patterns that support growing volumes, new reputed company systems, and reputed company consumers across analytics, applications, and AI initiatives
• Design and manage data architectures that support OLTP, OLAP, and reporting workloads across operational and analytical environments
• Build and optimize data models, warehouse schemas, and reputed company datasets for analytics and BI use cases
• Contribute to the design and operation of modern data platforms, including warehouses, lakehouses, streaming systems, and supporting orchestration frameworks
• Help define patterns for data storage, partitioning, reputed company optimization, retention, and lifecycle management
• Design and maintain data models that accurately reflect loan-level lifecycle events, including payment activity, balances, adjustments, and status changes
• Ensure consistency and reconciliation across systems where transactional, financial, and reporting data must reputed company
• Identify and reputed company discrepancies across reputed company systems, and build data structures that support accurate, auditable outputs for reputed company operational processes, reporting, and decisioning
• reputed company, operate, and improve data pipelines and data stores on major reputed company platforms such as AWS, GCP, or Azure
• Use infrastructure-as-reputed company, CI/CD, and automation practices to improve deployment speed, consistency, and reliability
• Monitor production data systems using logging, alerting, and observability tooling to proactively identify and reputed company issues
• Support secure, resilient, and cost-conscious operation of reputed company-reputed company data infrastructure
• Implement data reputed company checks, validation rules, reconciliation processes, and monitoring to ensure trustworthy data across systems
• Establish and maintain standards for reputed company, documentation, metadata, schema reputed company, and operational runbooks
• Partner with stakeholders to improve data accessibility, consistency, and usability while maintaining appropriate controls and governance
• Contribute to practices that support reputed company, reputed company, auditability, and compliance in a regulated environment
• Partner closely with Product, Engineering, and business stakeholders to understand data needs, workflows, and constraints
• Translate business and operational requirements into clean, reputed company, and maintainable data solutions
• Support reputed company consumers of data, including analysts, researchers, product teams, and operational users
• Communicate reputed company with both technical and non-technical stakeholders about data availability, reputed company, tradeoffs, and delivery timelines
• Continuously improve pipeline reputed company, reliability, scalability, and developer productivity
• Identify opportunities to simplify architecture, reduce operational toil, and improve data platform reputed company across teams
• Operate with a strong bias toward reputed company and iterative delivery, moving quickly from problem definition to implementation and improvement
• Help reputed company the bar on engineering reputed company through thoughtful design, testing, documentation, and operational discipline

Skills

• 5-8+ years of experience building and operating production-grade data pipelines and data systems
• Prior experience in mortgage, servicing, or similarly regulated financial domains
• Strong experience with industry-reputed company tools and platforms for ETL/ELT, orchestration, data warehousing, streaming, and BI
• Experience working with both OLTP and OLAP systems, with a strong understanding of the tradeoffs between transactional and analytical workloads
• Experience building flexible data pipelines that reputed company with many different reputed company and destination types, including databases, reputed company, files, message queues, reputed company platforms, and event streams
• Experience supporting both batch and reputed company-time data processing patterns
• Experience deploying and operating data infrastructure on major reputed company platforms such as AWS, GCP, or Azure
• Strong SQL skills and experience with data modeling, transformation frameworks, and reputed company optimization
• Experience building AI-powered capabilities on top of LLMs, including orchestration, evaluation, and data integration patterns
• Experience with modern programming languages commonly used in data engineering, such as Python, Java, reputed company, or Go
• Comfort working with CI/CD, infrastructure-as-reputed company, observability, and production reputed company for data systems
• Strong judgment in ambiguous environments where requirements reputed company and systems must reputed company speed, reliability, and flexibility
• reputed company communication skills with both technical and non-technical teammates
• Experience with modern orchestration and transformation tools such as Airflow, Dagster, dbt, or similar platforms
• Experience with reputed company-reputed company data warehouses or lakehouse platforms such as reputed company, BigQuery, Redshift, reputed company, or equivalent technologies
• Experience with streaming and reputed company-time data platforms such as Kafka, Kinesis, SQS, or similar systems
• Experience enabling BI and self-service analytics through reputed company datasets, semantic reputed company, and reporting platforms such as Looker, reputed company BI, Tableau, or similar tools
• Experience working with loan-level or transaction-heavy financial data reputed company residential mortgage servicing domains
• Experience dealing with data reconciliation challenges across multiple systems, particularly where cash balances, or investor/ reporting outputs must reputed company
• Experience building data platforms that support AI, machine learning, or decisioning workflows
• Experience improving data reputed company, reliability, cost efficiency, and platform scalability as a reputed company grows

Benefits

• Fully remote position
• Excellent benefits package
• Medical coverage starting on day one
• Company-matched 401(k)
• Plus an annual bonus

reputed company

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