Principal Software Developer - Data

Redfin is a technology-driven real estate company with the country's most-visited real estate brokerage website. As part of Rocket Companies (NYSE: RKT), Redfin is creating an integrated homeownership platform from search to close to make the dream of homeownership more affordable and accessible for everyone. Redfin’s clients can see homes first with on-demand tours, easily apply for a home loan with Rocket Mortgage, and save thousands in fees while working with a top local agent.

We are seeking a Principal Software Engineer to serve as the chief architect and technical north star for our enterprise data organization. In this role, you will design and scale a unified data platform that serves as the central nervous system for the entire company.

You will lead the transition to a modern, multi-tenant Data Lakehouse, abstracting away infrastructure complexity for our data engineers while democratizing high-performance, self-serve access for data scientists, machine learning engineers, and AI agents. You will partner with engineering directors and mentor Staff-level ICs to ensure our architecture scales elegantly securely across domain boundaries.

About the role 

• Lakehouse Architecture & Strategy: Design and implement a unified, open-format Data Lakehouse utilizing a Snowflake-managed Apache Iceberg architecture on AWS S3, transitioning the organization away from disjointed legacy data silos.

• Enterprise Data Ingestion: Architect and scale resilient, high-throughput ingestion frameworks. Design batch, micro-batch, and real-time streaming patterns to seamlessly extract data from diverse transactional databases, third-party APIs, and event logs, landing it reliably into our Bronze storage tier.

• Multi-Tenant Data Mesh Design: Architect a sovereign, domain-oriented data mesh within a single Snowflake environment. Implement delegated domain administration and sophisticated RBAC/Row-Access Policies to ensure strict infosec compliance without impeding cross-domain data sharing.

• Semantic Layer & AI Readiness: Spearhead the deployment of a Universal Semantic Layer on top of our Gold-tier data. Ensure business logic is defined as code to guarantee metric consistency across BI tools, data apps, and downstream LLM/AI agents.

• Data Flow & Pipeline Engineering: Define the technical standards for our Medallion (Bronze, Silver, Gold) data flow. Standardize modern ELT patterns utilizing dbt, PySpark, and Snowpark to handle petabyte-scale transformations efficiently.

• Infrastructure & Automation: Drive a rigorous Infrastructure-as-Code (IaC) culture using Terraform for all platform provisioning, networking, and security configurations.

• Technical Leadership: Act as the ultimate technical escalation point for an organization of 60+ engineers. Mentor Staff and Senior Individual Contributors, lead architecture design reviews, and establish engineering best practices.

• Cross-Organization Collaboration: Act as the primary technical liaison to Principal Architects across the broader organization. Define robust integration contracts and connection points between upstream transactional systems, the data platform, and downstream product applications, ensuring a unified, highly interoperable enterprise architecture.

About you 

Required Qualifications

• Experience: 12+ years of software/data engineering experience, with at least 5+ years operating at a Staff, Principal, or Lead Architect level.

• Cloud & Lakehouse Expertise: Deep, hands-on architectural experience with AWS (S3, IAM, EKS) and Snowflake. Proven experience implementing open table formats, specifically Apache Iceberg.

• Data Ingestion & ELT: Deep expertise with modern data movement pipelines (e.g., Fivetran, Airbyte) and high-velocity event-streaming platforms (e.g., Apache Kafka, AWS Kinesis, Snowpipe). Experience migrating legacy ETL platforms to modern, compute-optimized ELT architectures is highly preferred.

• Data Modeling: Expert understanding of modern data modeling techniques, including Star Schema design for highly optimized analytical reads and dimensional modeling for enterprise semantic layers.

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