Remote Data & Analytics Engineering Manager

Limble CMMS; Charlotte (NC); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Comprehensive health, dental, and/or/…

Employer-paid life insurance

Employer-paid short-term disability

401(k) with company match

HSA with employer contributions

Flexible Spending Accounts

Monthly wellness stipend

Fully remote position

Flexible PTO

13 paid company holidays

Paid parental leave

Health, Dental, and Vision insurance

Job summary

Limble is building a dedicated data and analytics capability within its engineering organization. As the Software Engineering Manager for Data & Analytics, you will own the strategy for collecting, storing, and surfacing data to power customer insights across the platform.

You’ll guide decisions on AI tooling and architect a scalable analytics foundation for product teams. You will start with a small team, grow it, and shape hiring, data architecture, and delivery standards.

Qualifications

• 5+ years in data engineering, analytics with at least 2 years in an engineering management or technical lead role.
• Experience designing data infrastructure on AWS (Aurora PostgreSQL, DynamoDB, Redshift, S3, and related services)
• Strong understanding of when to use an operational data store vs. an analytical one, and how to design the pipeline between them
• Strong background in data modeling, ELT/ETL pipeline design, and building analytics-ready datasets
• Experience building or contributing to a reporting or analytics framework consumed by multiple engineering teams or product surfaces
• Experience owning data pipeline observability such as monitoring, alerting, SLAs, and incident response for data freshness and quality issues
• Actively leveraging AI coding tools (GitHub Copilot, Cursor, Claude, or similar) in day-to-day development and sets the expectation for the team to do the same
• Some exposure with embedding AI driven capabilities inside of a SaaS product
• Comfortable staying player-coach: you can write a design doc, review a schema, or weigh in on a query optimization
• Track record of hiring and developing engineers; you know what a good data engineer looks like and can get them excited about our mission here at Limble
• Strong communicator who can translate data architecture decisions into language product and business stakeholders actually understand
• Bias toward simplicity over complex solutions
• Located in or near the Charlotte, NC metro area

Responsibilities

• Define and drive the strategy for Limble's analytical data infrastructure
• Design the boundary between transactional data stores (what the product reads and writes against) and the analytical layer (what feeds reporting and ai-powered insights), keeping both performant and maintainable
• Architect and own the reporting framework that stream-aligned engineering teams use to embed analytics into their product areas
• Partner with product leadership to translate customer and business analytics needs into a technical roadmap
• Build, hire, and lead a high-performing team of data and analytics engineers
• Drive significant architectural decisions through ADR reviews with Principal and Staff engineers, bringing well-reasoned proposals and leading the conversation
• Own the observability of your data pipelines by defining SLAs for data freshness and quality, build alerting, and keep your consumers informed when something's off
• Establish data governance and quality standards so the rest of engineering can trust the data they're building on top of
• Drive adoption of the reporting framework across stream-aligned teams
• Stay hands‑on enough to review critical design decisions, contribute to architecture, and help your team get unstuck

Skills

Data engineering

Analytics engineering

Team leadership

Hiring engineers

Communication with stakeholders

Tools

AWS

Job description

Limble is building a dedicated data and analytics capability within its engineering organization. As the Software Engineering Manager for Data & Analytics, you will own the strategy for collecting, storing, and surfacing data to power customer insights across the platform.

You’ll guide decisions on AI tooling and architect a scalable analytics foundation for product teams. You will start with a small team, grow it, and shape hiring, data architecture, and delivery standards.