[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 to enhance their data reputed company for analytics and operational decision-making. The role involves designing and maintaining data systems, ensuring data reputed company, and collaborating with various stakeholders to support business needs.

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 curated 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, performance 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 resolve 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 resolve issues
• Support secure, resilient, and cost-conscious operation of reputed company-based 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 performance, 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 performance 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 operations for data systems
• Strong judgment in ambiguous environments where requirements reputed company and systems must balance 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 curated datasets, semantic reputed company, and reporting platforms such as Looker, Power 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 system 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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