Staff Data Infrastructure Engineer — Scale AI Analytics

Lightfield; Cambridge (MA); On-site; USD 180,000 - 300,000; Full time

Benefits offered by this job

Competitive salary

Meaningful early equity

Health insurance (medical, dental, and

3 weeks of PTO

11 paid company holidays

3 months of paid family leave

Wednesdays work from home

401k plan

Commuter and lunch stipend

Job summary

Lightfield, an AI-native CRM, is building the data infrastructure that powers hundreds of dashboards and customer analytics in Cambridge (HQ SF option). We’re hiring a Staff Engineer, Data Infrastructure, to scale the analytics path, design ingestion, and shape the data model for fast, reliable queries at scale.

You’ll own production data systems with high-volume workloads, contribute across backend systems, and help set engineering practices as the team grows, aligning product needs with robust

Qualifications

• 7+ years of software engineering experience.
• Experience owning production data systems with user-facing impact.
• Ability to debug across multiple stack layers.

Responsibilities

• Scale the analytics engine behind dashboards with strong query performance.
• Design ingestion paths, event models, schemas and queries.
• Evolve a schema-flexible data model for fast queries.
• Build foundations for historical reporting and auditability.
• Set technical direction and engineering practices for data systems.

Skills

Software engineering fundamentals

Production data systems

Data freshness

Debugging across stack

Product orientation

Ownership & communication

Tools

Postgres

Redis

Typesense

BullMQ

Job description

Lightfield, an AI-native CRM, is building the data infrastructure that powers hundreds of dashboards and customer analytics in Cambridge (HQ SF option). We’re hiring a Staff Engineer, Data Infrastructure, to scale the analytics path, design ingestion, and shape the data model for fast, reliable queries at scale.

You’ll own production data systems with high-volume workloads, contribute across backend systems, and help set engineering practices as the team grows, aligning product needs with robust