[Hiring] Data Engineer @Lakeview Loan Servicing

Role Description

The Data Engineer on the Nebula team plays a critical role in building and evolving the data foundation that powers analytics, reporting, AI development, and operational decision-making across the organization. This role is responsible for designing, building, and maintaining reliable, scalable, and flexible data systems that support a wide range of internal and external use cases.

• Working across data ingestion, transformation, storage, modeling, and delivery.
• Partnering closely with Product, Engineering, AI, Analytics, and domain Subject Matter Experts (SMEs).
• Translating complex business processes and data needs into production-ready data pipelines and platforms.
• Contributing to the development and evolution of core data capabilities, including batch and real-time pipelines, operational and analytical data stores, semantic models, and BI-ready datasets.
• Operating effectively in a modern engineering environment using automation, observability, and infrastructure-as-code practices.
• Ensuring that data is trustworthy, accessible, and fit for purpose.

Responsibilities

• Data Pipeline Development:
  • Design, build, and maintain robust data pipelines for a wide variety of input and output sources.
  • Develop scalable ETL and ELT workflows for both batch and real-time processing.
  • Ensure pipelines are reliable, testable, observable, and easy to extend as business needs evolve.
  • Build reusable data integration patterns that support growing volumes, new source systems, and downstream consumers.
• Data Platform & Storage:
  • Design and manage data architectures that support OLTP, OLAP, and reporting workloads.
  • 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.
  • Help define patterns for data storage, partitioning, performance optimization, retention, and lifecycle management.
• Cloud Deployment & Operations:
  • Deploy, operate, and improve data pipelines and data stores on major cloud platforms.
  • Use infrastructure-as-code, CI/CD, and automation practices to improve deployment speed, consistency, and reliability.
  • Monitor production data systems using logging, alerting, and observability tooling.
  • Support secure, resilient, and cost-conscious operation of cloud-based data infrastructure.
• Data Quality, Reliability & Governance:
  • Implement data quality checks, validation rules, reconciliation processes, and monitoring.
  • Establish and maintain standards for lineage, documentation, metadata, schema evolution, and operational runbooks.
  • Partner with stakeholders to improve data accessibility, consistency, and usability.
  • Contribute to practices that support security, privacy, auditability, and compliance.
• Cross-Functional Collaboration:
  • Partner closely with Product, Engineering, and business stakeholders to understand data needs.
  • Translate business and operational requirements into clean, scalable, and maintainable data solutions.
  • Support downstream consumers of data, including analysts, researchers, product teams, and operational users.
  • Communicate clearly with both technical and non-technical stakeholders about data availability, quality, tradeoffs, and delivery timelines.
• Iteration & Continuous Improvement:
  • Continuously improve pipeline performance, reliability, scalability, and developer productivity.
  • Identify opportunities to simplify architecture, reduce operational toil, and improve data platform leverage.
  • Operate with a strong bias toward action and iterative delivery.
  • Help raise the bar on engineering quality through thoughtful design, testing, documentation, and operational discipline.

Qualifications

• 2-4+ years of experience building and operating production-grade data pipelines and data systems.
• Strong experience with industry-standard tools and platforms for ETL/ELT, orchestration, data warehousing, streaming, and BI.
• Experience working with both OLTP and OLAP systems.
• Experience building flexible data pipelines that integrate with many different source and destination types.
• Experience supporting both batch and real-time data processing patterns.
• Experience deploying and operating data infrastructure on major cloud platforms.
• Strong SQL skills and experience with data modeling, transformation frameworks, and performance optimization.
• Experience with modern programming languages commonly used in data engineering.
• Comfort working with CI/CD, infrastructure-as-code, observability, and production operations for data systems.
• Clear communication skills with both technical and non-technical teammates.

Preferred Experience

• Experience with modern orchestration and transformation tools.
• Experience with cloud-native data warehouses or lakehouse platforms.
• Experience with streaming and real-time data platforms.
• Experience enabling BI and self-service analytics through curated datasets.
• Experience in fintech, mortgage, lending, payments, insurance, or other regulated domains.
• Experience building data platforms that support AI, machine learning, or decisioning workflows.

Benefits

• Competitive salary range of $220,000 to $300,000, plus an annual bonus.
• Medical coverage starting on day one.
• Company-matched 401(k).

A note to candidates

You do not need prior fintech or finance experience to succeed in this role. If you are a strong data engineer with solid technical judgment, a systems mindset, and excitement for solving complex data problems, we would love to hear from you.

If your background does not line up perfectly with every bullet, but this role feels like the kind of work you want to do, please apply.

Bayview is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law.