Director of Data Engineering – 100% Remote

Company Description

Hyly.AI is multifamily’s only Intelligence Fabric™, weaving Artificial, Business, and Human intelligence into one operating system for growth. The company connects raw data to decisions, decisions to actions, and actions to measurable outcomes, turning complexity into clarity. Founded in 2010, Hyly.AI has been helping multifamily leaders scale operations and marketing without adding extra headcount. Today, 4 of the top 5 National Multifamily Housing Council (NMHC) managers rely on Hyly.AI to power their growth by transforming data into actionable insights and structured processes.

Role Description

The Director of Data Engineering leads the design and operation of Hyly.AI’s real-time data platform—building high-throughput streaming systems that power analytics and product features across the Web Fabric and backend APIs. This leader manages 10+ engineers and drives architecture excellence for scalability, latency, and resilience.

Job Responsibilities :

Define the real-time data architecture (ingestion, processing, serving) to meet product SLAs.

Lead teams of 10+ engineers responsible for streaming pipelines and feature stores.

Author architecture and design documents for cross-functional review.

Implement best practices for data quality, governance, and observability.

Collaborate with Frontend, ML and API teams to enable low-latency real-time features.

Optimize cost, performance, and incident response for streaming systems.

Mentor senior engineers and build next-generation technical leaders.

Must Have Qualifications :

6+ years in engineering (2+ in data / real-time leadership roles).

Track record of building production-grade real-time data pipelines.

Experience with Kafka, Pulsar, Flink, or equivalent streaming tech.

Strong operational discipline (SLAs, monitoring, incident response).

Excellent architecture documentation and cross-team communication skills.

Nice to Have Qualifications :

Knowledge of feature stores, real-time analytics, and ML serving.

Experience integrating streaming data with frontend dashboards and APIs.

Understanding of cost optimization and data observability tooling.