Data Engineer

Radix is building the most trusted data and analytics platform in multifamily. Joining now means stepping into a place where curiosity wins, ideas move quickly, and your impact shapes an industry. We’re looking for a highly capable, hands-on Data Engineer to help build the foundation for Radix’s next generation of data and AI products. This is a strong individual contributor role for someone who wants to solve hard data problems, build reliable systems, and raise the bar for how data moves, models, and powers decision-making across the business.

Responsibilities

Design, build, and maintain scalable ETL/ELT pipelines that ingest data from files, databases, APIs, and third-party systems into trusted, analytics-ready data products.; Own the reliability, performance, governance, and cost optimization of Radix's Databricks-based data platform, including orchestration, data quality, observability, and root cause analysis.; Build and maintain robust dbt models, testing frameworks, documentation, schema contracts, and semantic-layer assets that create trusted, scalable data products.; Define and enforce data contracts, metric definitions, and modeling standards that support consistent use across analytics, product, and AI applications.; Partner across teams to design reliable, governed data interfaces and ensure downstream consumers can confidently use and trust the data they depend on.; Help build the semantic layer and AI data infrastructure that powers conversational analytics, LLM-driven experiences, and agentic workflows.; Design and maintain metadata, business definitions, evaluation frameworks, and governance guardrails that improve the trustworthiness of AI-generated insights.; Build and maintain infrastructure-as-code, CI/CD pipelines, automated testing, and deployment practices that enable reliable and scalable data platform operations.; Improve developer experience through better tooling, local development workflows, testing practices, environment consistency, and deployment confidence.; Implement production-grade monitoring, lineage, anomaly detection, alerting, and operational processes that proactively identify and resolve data issues.; Create documentation, runbooks, and operational playbooks that improve platform supportability, knowledge sharing, and long-term scalability.; Operate as a highly collaborative technical leader who aligns stakeholders, documents decisions, and helps drive a reliable, scalable, and AI-ready data ecosystem.

Requirements

5+ years of experience in Data Engineering, Analytics Engineering, or a related field, with hands-on responsibility for production data platforms and pipelines.; Deep expertise with Databricks (or similar modern data platforms), dbt, SQL, Python, and scalable data modeling, including governance, testing, documentation, and semantic layers.; Experience building and maintaining reliable data pipelines from relational databases, document stores, and object storage using modern table formats such as Delta Lake, Iceberg, and Parquet.; Strong understanding of cloud-based data infrastructure, including AWS, Terraform, CI/CD, orchestration platforms (Dagster, Airflow, or similar), observability, monitoring, lineage, and data quality frameworks.; Comfortable working in hybrid-cloud environments and making sound decisions around architecture, performance, cost optimization, reliability, and operational readiness.; Able to trace and resolve data issues end-to-end, implement effective data contracts, and identify risks or anti-patterns in modeling, pipeline design, and system operations before they become problems.; Comfortable navigating ambiguity, simplifying complex systems, and improving data quality and engineering practices without slowing delivery.; Actively leverage AI tools and understand how modern development practices, automation, and agentic workflows can improve engineering productivity while maintaining trust, accuracy, and governance.; Familiar with designing data platforms that support analytics, applications, and AI use cases through clean ontologies, predictable schemas, semantic layers, and trustworthy metrics.; Hands-on builder who leads through technical credibility, strong communication, collaboration, and sound judgment rather than authority.; High ownership mindset with a track record of delivering meaningful improvements in fast-moving, evolving environments.; Excited by the opportunity to build reliable, understandable, and scalable data systems that create measurable value for humans, applications, and AI agents.

Benefits

Medical, dental and vision coverage; Uncapped Paid Time Off; Pre-IPO Equity; Performance Bonus; Learn From the Best; Build Category-Defining Products