Core Engineer - Data Systems

Sourcedirect Talent•Denver, CO

5d•Hybrid

About The Position

Our client is seeking a Core Engineer focused on data systems to build the streaming and data foundations that power a next-generation edge platform. In this role, you will own core platform capabilities for ingesting, contextualizing, and serving customer data across OT/IT environments, while also supporting internal data systems that enable observability, alerting, inventory, configuration, fleet state, and deployment telemetry. You will define and enforce data contracts and integration standards, ensuring production data is accurate, traceable, and trustworthy for both AI and operational use cases. This is a hands-on, high-ownership role ideal for engineers who want to build the infrastructure that makes real-world AI deployments reliable and scalable.

Requirements

6+ years building and operating production data, streaming, or integration systems
Experience running real-time pipelines with strong reliability practices (e.g., Kafka-style systems, observability, on-call readiness, incident response)
Strong engineering fundamentals with clean, well-documented implementations
Proficiency in Python and/or Go, APIs for ingestion/access, and structured testing
Comfortable navigating ambiguity and making sound trade-offs under real-world constraints
Strong communicator and cross-functional collaborator
Ownership mindset focused on outcomes

Nice To Haves

Production experience with streaming and event-driven systems (e.g., Kafka)
Experience with federated query systems and large-scale analytics access patterns (e.g., Trino)
Background integrating data across OT/IoT environments (MQTT, OPC UA, Modbus, DNP3)
Experience building trusted data systems with contracts, validation, and lineage
Track record of turning complex customer integrations into repeatable platform capabilities

Responsibilities

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
Implement and operate real-time streaming and event-driven data flows with clear failure modes
Define and enforce data contracts, schemas, and integration standards
Ensure end-to-end data accuracy, lineage, auditability, and validation
Build and support internal data systems including: Observability pipelines, Alerting systems, Inventory and configuration databases, Fleet telemetry
Design scalable query and access patterns supporting analytics and AI workloads
Partner with customer-facing teams to translate requirements into durable platform capabilities
Produce clear engineering documentation and reusable artifacts
Leverage AI tools to accelerate development while maintaining rigorous production review