About the role

You will own the development and maintenance of core data systems, including ingestion, streaming, and observability across hybrid environments. You will also define data contracts and integration standards to ensure reliable, scalable, and trustworthy data flows for AI and operational systems.

What they look for

Data systems Streaming systems Kafka Python Go Observability Data contracts Integration patterns OT/IoT protocols System design Cloud infrastructure Data lineage Federated query Time-series data API development Production engineering

Requirements

The role requires 6+ years of experience in building production-grade data or streaming systems with strong operational reliability. Candidates must be proficient in Python or Go and possess the ability to design scalable, observable architectures in complex environments.

Benefits

Health insurance Dental coverage Vision coverage 401(k) with company match Flexible PTO Paid parental leave Commuter benefits Relocation support Visa support Stock options

Full description

Core Engineer — Data Systems (Multiple Levels)

Hybrid — Denver, CO Full-time

The Opportunity

We’re looking for a Core Engineer focused on data systems to build the data and streaming foundations that make a real-world technology platform reliable, observable, and repeatable.

You’ll own core platform capabilities for ingesting, contextualizing, and serving customer data across OT/IT environments. You’ll also build and support internal data systems that power platform operations, including observability, alerting, inventory, configuration, fleet state, and deployment telemetry.

This role defines and enforces data contracts and integration standards, ensuring that data flows are production-ready. You’ll help ensure data is accurate, traceable, and trustworthy for both AI-driven and operational systems.

You’ll partner with software, infrastructure, security, and commercial teams to translate requirements and feedback into durable platform capabilities that scale. This is an AI-native environment where AI tools are used to accelerate development and troubleshooting while maintaining rigorous review and auditability for production data paths.

This is a hands-on opportunity for someone who thrives in a high-ownership setting and wants to build the infrastructure that supports real-world AI applications.

What You’ll Do

Own core capabilities for ingesting, contextualizing, and serving data across edge and hybrid environments.

Build and evolve connectors and integration patterns across OT/IoT protocols and enterprise systems, with strong reliability and observability.

Implement and operate real-time streaming and event-driven data flows for low-latency use cases with clearly defined failure modes.

Define and enforce data contracts, schemas, and integration standards so producers and consumers operate predictably.

Ensure data accuracy and traceability end-to-end, including lineage, auditability, and validation mechanisms.

Build and support internal data systems for platform operations, including observability pipelines, alerting, inventory and configuration databases, and fleet telemetry.

Design scalable query and access patterns that support analytics and AI, including federated query and time-series access patterns.

Partner with customer-facing teams to understand requirements and feedback, then translate those learnings into durable platform capabilities.

Maintain clear engineering documentation and reusable artifacts, using AI tools to accelerate implementation, debugging, and iteration while applying sound engineering judgment and rigorous production review.

What Success Looks Like

In your first 3 months, you will have:

Shipped a critical data system, either customer-facing or internal, that delivers measurable improvements in reliability, latency, observability, or integration speed.

Established clear data contracts and validation mechanisms for at least one production-critical data flow, improving trust, traceability, and operational confidence.

Earned trust through autonomy and execution, becoming the go-to owner for a meaningful portion of the data platform or internal telemetry systems.

In your first year, you will be:

Owning major components of the data platform and internal data systems end-to-end, with clear accountability for production outcomes and reliability.

Driving improvements that make integrations faster, safer, and more repeatable across deployments.

Shaping platform direction through scalable patterns across connectors, streaming, semantics, governance, and observability that enable new AI and operational use cases.

Who You Are

6+ years of experience building and operating production data systems, streaming systems, or integration platforms across complex environments.

Experience operating real-time pipelines with strong reliability practices, such as Kafka-style event systems, robust observability and alerting, on-call readiness, incident response, and clearly defined failure modes.

Strong engineering craft, including clean implementations, thoughtful system design, operational clarity, and strong documentation.

Experience with technologies such as Python and/or Go, ingestion and access APIs, and structured testing.

Comfortable working in ambiguous environments and making sound trade-offs under real-world constraints involving latency, bandwidth, security, deployment timelines, and operational risk.

Clear communicator and strong collaborator across engineering and customer-facing teams.

Ability to define standards and enforce production discipline.

Ownership mindset focused on outcomes rather than tasks.

Unique Experiences We Value

Production experience with streaming and event-driven systems, such as Kafka, and operating them reliably under real-world constraints.

Experience with federated query systems and large-scale analytics access patterns, such as Trino, supporting both operational and AI workflows.

Experience building data integrations for OT/IoT environments, including protocols such as MQTT, OPC UA, Modbus, and DNP3.

Experience handling schema drift, data quality, and connectivity variability.

Experience building trusted data systems with contracts, validation, and lineage, including schema enforcement, traceability, auditability, and mechanisms to prevent unsafe production data paths.

Experience partnering with customer-facing teams to turn complex integrations and requirements into repeatable platform capabilities.

Strong focus on keeping production systems reviewed, auditable, and operationally sound.

Benefits & Compensation

Work in a high-ownership, real-world startup environment where you can move quickly, build new systems, and see your impact directly.

Use modern AI tools throughout development, documentation, troubleshooting, and deployment workflows to accelerate iteration and execution.

Take on challenging technical problems at the intersection of infrastructure, cloud, IoT, hardware/software systems, networking, data, and AI.

Collaborate with exceptional teammates and industry leaders across software, AI, and infrastructure.

This role may be filled at either the Senior or Staff level.

Base salary range:

Senior: $130,000–$155,000

Staff: $160,000–$185,000

Eligibility for meaningful equity through stock options in an early-stage, high-growth company.

Eligibility to participate in company benefit plans, which may include health, dental, and vision coverage, a 401(k) with company match, flexible PTO, paid parental leave, commuter benefits, and relocation and visa support for eligible roles.