Senior Software/Data Engineer
At a glance
Senior Data Engineering role at cinc. Atlanta · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Design distributed systems that stay fault-tolerant while balancing consistency with availability
- Choose databases for each workload, then shape schemas, indexes and queries for fast data access
- Build and monitor high-volume ETL/ELT pipelines that preserve data accuracy from source through delivery
- Find performance bottlenecks by profiling memory, processor and network use, then add tracing and profiling
- Lead proof-of-concept work, record architecture choices and mentor junior engineers
What you bring
- You understand distributed-system concepts such as idempotence, consistency models and consensus
- You can work with database storage engines, row and column formats, and storage tiering
- You have hands-on experience with Kafka, Pulsar or Kinesis, plus strong Python skills
- You are comfortable using Kubernetes and CI/CD for data workflows, and know relational and analytical databases
Who this fits
This senior individual-contributor role suits an engineer who can own ambiguous technical problems through implementation and guide junior teammates. You’ll work full time, Monday through Friday, with two weekly office days in the Atlanta area. Applicants must be authorized to work in the United States; visa sponsorship is unavailable.
From the employer
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.