Senior Software/Data Engineer

Job description

Senior Software/Data Engineer Role Overview At CINC, we power the elite of real estate. As a Senior Software/Data Engineer on the TruBase platform, you will own the data transport, transformation, modeling, and analytics of real estate data points that drive institutional-grade insights for top-tier real estate professionals and organizations. We are looking for someone who understands software architecture design patterns and data modeling, including entity resolution at scale — building systems where data integrity is non-negotiable. The right candidate takes full ownership of their work, brings genuine curiosity to hard problems, and thrives as a highly skilled problem solver who can navigate ambiguity and drive solutions end-to-end. Essential Responsibilities Architect Distributed Systems: Design and scale fault-tolerant systems that balance consistency and availability. Database Engineering: Evaluate and implement database technologies based on workload needs. You will own schema design, indexing strategies, and query optimization to ensure low-latency data access. High-Throughput ETL/ELT: Build, monitor, and maintain "correct-by-design" pipelines. You’ll ensure data integrity across the lifecycle of our high-volume data flows. System Observability & Profiling: Proactively identify bottlenecks by analyzing memory, CPU, and network usage. You will implement distributed tracing and profiling to keep the system lean. Technical Leadership: Drive innovation through Proof-of-Concepts (PoCs), document architectural decisions, and provide technical mentorship to junior engineers. Technical Competencies & Experience Core Requirements Distributed Systems: Deep understanding of idempotence, consistency models, and consensus protocols. Database Internals: Functional knowledge of storage engines (B+ Trees vs. LSM trees), storage formats (Columnar vs. Row), and tiering. Performance Engineering: Proficiency in debugging and profiling tools (e.g., strace, py-spy, Flamegraphs) to optimize IO and CPU usage. Data Streaming: Hands-on experience with log-based distributed systems such as Kafka, Pulsar, or Kinesis. Modern Tooling: Strong Python skills and comfort with Kubernetes and CI/CD for data workflows. Experience with TypeScript is a plus. Database Diversity: Familiarity with both relational and analytical stores (e.g., Postgres, Redshift, Clickhouse, DynamoDB). Our Stack (what you'll work in day-to-day): Python · ClickHouse · PostgreSQL · Kafka · Kubernetes Preferred (Nice-to-Have) Experience with lower-level languages (e.g., Rust, Go, or C++). Deep understanding of serialization codecs and compression (Protobuf, FlatBuffers). Knowledge of AWS Cloud Architecture and Data Governance frameworks. How We Measure Success System Reliability: Maintaining high uptime and scalability metrics under peak loads. Performance Gains: Measurable improvements in query latency and pipeline throughput. Architectural Integrity: Delivery of clean, well-documented code and system designs. Team Growth: Positive impact on the technical growth and velocity of the broader engineering team. Other Information: Supervisory Responsibility: This position has no direct reports. Reports to: VP of Data Position Type/Expected Hours of Work This is a full-time position; days and hours of work are Monday through Friday, 40 hours a week. (Hybrid, Atlanta Area — 2 Days/Week in Office) Work Authorization:Applicants must be legally authorized to work in the United States for any employer. We are unable to provide visa sponsorship (e.g., H-1B, OPT extensions) at this time. This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice.