About Radix Radix is a fast‑growing SaaS company serving the multifamily industry with actionable data and insights. Our values-Curiosity, Resilience, Impact, Courage, and Responsibility-are at the heart of how we operate and grow. At Radix, our data is our super‑power: from benchmarking rents to powering predictive analytics, everything we build starts with clean, reliable, and accessible data. We believe exceptional people build exceptional companies, and our Data Engineer will be a cornerstone in scaling the pipelines and platforms that turn raw information into industry‑shaping intelligence. Your Impact As a Data Engineer, you will design, build, and optimize the data infrastructure that fuels Radix's AI/ML models, dashboards, and customer‑facing products. Working hand‑in‑hand with data scientists, product managers, and software engineers, you'll make certain the right data shows up in the right place at the right time-securely, accurately, and efficiently. Your solutions will directly shape how thousands of multifamily professionals discover insights and make data‑driven decisions. Key Outcomes Reliable Data Pipelines - Deliver highly available, low‑latency ETL/ELT pipelines that ingest and transform high-volume records with efficiency Scalable Architecture - Implement cloud‑native patterns (e.g., CDC, stream processing, lake‑house) that can scale with the business Data Quality & Governance - Achieve automated data‑quality coverage through testing, monitoring, and alerting, reducing manual fixes Cross‑Team Enablement - Provide self‑service data access that accelerates analytics and model training cycles Key Responsibilities * Design ETL/ELT workflows using Python, SQL, and orchestration tools (Airflow, Prefect, Dagster) to ingest data from APIs, files, and third‑party feeds * Engage with complex business challenges and design innovative, scalable data solutions that unlock insight and drive strategic outcomes * Develop and maintain data lakes and warehouses (Snowflake, BigQuery, Redshift, or similar) following lake‑house principles, partitioning, and cost‑optimization best practices * Leverage Kafka, Kinesis, or Pub/Sub to process real‑time data for event‑driven features and analytics * Embed tests and monitoring to catch anomalies early; champion data‑governance standards * Partner with data scientists to produce features; work with backend engineers to surface data via APIs; liaise with DevOps on CI/CD and infrastructure‑as‑code (Terraform, Pulumi) * Enforce data‑security, privacy, and compliance (SOC 2) across pipelines and storage layers * Track performance metrics, conduct root‑cause analysis on incidents, and iterate rapidly in sprints What You Bring Experience * 3-8 years in data engineering or related backend engineering roles within cloud‑based environments * Proven track record designing and operating production‑grade data pipelines supporting analytics or ML workloads Skills * Expert in Python and advanced SQL; comfortable with Spark * Hands‑on with modern orchestration (Airflow/Prefect/Dagster) and version‑controlled ELT frameworks (dbt) * Depth in at least one cloud ecosystem (AWS, GCP, or Azure) and containerization (Docker, Kubernetes) * Familiarity with CI/CD and infrastructure‑as‑code (Terraform, CloudFormation) * Strong grasp of data‑modeling, performance tuning, and cost‑optimization * Excellent communication and collaboration skills to translate business needs into technical solutions Preferred * Experience supporting AI/ML pipelines or MLOps tooling (Feature Store, MLflow) * Exposure to property tech, real‑estate, or other asset‑heavy industries * Knowledge of Data Mesh or domain‑oriented data product principles Personal Attributes Curiosity - You ask "why" relentlessly and love exploring new tech. Resilience - You keep systems stable under load and bounce back quickly from incidents. Impact‑Focused - You measure success by business value delivered, not lines of code written. Courage - You're willing to refactor boldly and advocate for best practices. Responsibility - You own your pipelines end‑to‑end-from design to on‑call. How We Work at Radix We thrive in an environment built on trust and collaboration. Micromanagement isn't our style; outcome‑ownership is. Our values guide every sprint, stand‑up, and architectural decision. You'll have the autonomy to innovate and the support of teammates who care deeply about quality and customer impact.