System Engineer - Solution Integrations

NOV • Houston, TX

8d

About The Position

This role focuses on owning technical readiness across DaaS and partner application integrations. The System Engineer will define repeatable architecture patterns for industrial data services, covering edge systems, control system data, cloud services, partner platforms, customer endpoints, and platform services. Key responsibilities include creating reference architectures, integration diagrams, data flow views, deployment patterns, validation plans, and technical readiness checklists. The role also involves defining the technical baseline for secure data acquisition, buffering, monitoring, cloud processing, customer delivery, and steady-state support, while proactively identifying integration gaps, network constraints, cybersecurity requirements, vendor dependencies, and operational risks before PoCs or pilots commence. Additionally, the engineer will create reusable cybersecurity and OT evidence packages for customer reviews, maintain standard documentation for network configurations and security, and support customer approval processes. Data standards, assurance, and quality monitoring are crucial, as is defining processes for historical data management and validation. The role includes defining pre-PoC validation gates, validating system readiness, and developing repeatable validation procedures and troubleshooting methodologies. Vendor and partner coordination is essential for defining integration responsibilities and ensuring partner platforms align with NOV service wrappers. The engineer will support architecture and readiness for data movement from edge to cloud, lead technical investigations, and partner with various internal teams to make deployments repeatable and supportable. Driving technical improvements to reduce complexity and one-off work, and maintaining integration documentation and governance are also key aspects of this position. The use of AI-assisted tools to accelerate tasks is encouraged, provided sound engineering judgment is applied.

Requirements

• Bachelor's degree in Engineering, Computer Science, Information Systems, Industrial Technology, Data Systems, or related field.
• 5+ years of experience in systems engineering, integration engineering, solution engineering, technical architecture, industrial digital systems, or customer facing technical delivery.
• Experience designing or validating integrations across edge systems, cloud services, APIs, data flows, partner systems, and customer delivery endpoints.
• Experience with industrial data systems, operational data flows, OT and IT integration, industrial edge and cloud platforms, or rig and site data environments.
• Experience working with vendors, partners, engineering teams, implementation teams, support teams, and customer facing stakeholders.
• Strong technical fluency across edge to cloud architectures, networking, APIs, authentication, observability, cybersecurity, and operational data systems, including experience troubleshooting connectivity, security, data quality, and integration issues in distributed OT and IT environments.
• Working knowledge of networking and OT and IT concepts such as TCP/IP, VLANs, routing, firewall rules, VPNs, DMZ design, segmentation, and secure remote access.
• Working knowledge of industrial data protocols and interfaces such as WITSML, ETP, WITS, OPC UA, Modbus, MQTT, REST APIs, customer historians, or industrial data platforms.
• Experience with data quality concepts such as latency, completeness, frequency, validity, source versus target comparison, mapping, units of measure, and real time data workflows.
• Strong Linux administration and command line troubleshooting experience.
• Experience using API and network diagnostic tools such as Postman, curl, Wireshark, tcpdump, and related troubleshooting utilities.
• Demonstrated ability to analyze logs, validate end to end data flows, isolate root causes, and drive technical issues to resolution across complex distributed systems.
• Experience identifying technical readiness risks before customer PoCs, pilots, or deployments begin.
• Ability to create reference architectures, data flow diagrams, validation plans, integration checklists, and technical decision records.
• Strong understanding of network, cybersecurity, access, data quality, auditability, service operations, and supportability considerations in integration heavy environments.
• Ability to communicate technical tradeoffs clearly to technical teams, commercial stakeholders, partners, and customer facing teams.
• Strong bias toward repeatable patterns, documentation, validation, and reducing one off integration work.

Nice To Haves

• Experience leveraging AI assisted tools to accelerate troubleshooting, architecture reviews, integration design, documentation, and solution validation while applying sound engineering judgment to validate results.

Responsibilities

• Own technical readiness across DaaS and partner application integrations.
• Define repeatable architecture patterns for industrial data services across edge systems, control system data, cloud services, partner platforms, customer endpoints, and platform services.
• Create reference architectures, integration diagrams, data flow views, deployment patterns, validation plans, and technical readiness checklists.
• Define the technical baseline for secure data acquisition, buffering, monitoring, cloud processing, customer delivery, and steady state support.
• Identify integration gaps, network constraints, cybersecurity requirements, vendor dependencies, and operational risks before PoCs or pilots begin.
• Create reusable cybersecurity and OT evidence packages for customer IT and OT reviews.
• Maintain standard topology diagrams, data flow diagrams, firewall rule templates, DMZ, VLAN, VPN, and routing patterns, identity and access assumptions, logging evidence, and remote access patterns.
• Support customer cybersecurity, MoC, and OT approval processes with clear technical documentation and repeatable review artifacts.
• Ensure integration patterns account for segmentation, auditability, hardening, patching, remote access, change control, and customer approval expectations.
• Define standards for source to target data assurance, data mapping, customer naming conventions, unit handling, latency, completeness, frequency, validity, and source versus target comparison.
• Define how data quality signals are monitored, surfaced, alerted, and acted on across internal teams and customer facing workflows.
• Support standards for historical backfill, replay, corrected history workflows, local versus cloud historian boundaries, and customer delivery validation.
• Create reusable templates for customer standards management, data mapping, endpoint setup, and delivery validation.
• Define pre PoC validation gates for customer and partner opportunities.
• Validate that required systems, data sources, endpoints, access paths, network assumptions, and support expectations are understood before delivery begins.
• Create repeatable technical validation plans for PoCs, pilots, partner integrations, and production deployments.
• Develop repeatable validation procedures, troubleshooting methodologies, and diagnostic playbooks that improve deployment success, reduce integration risk, and accelerate issue resolution.
• Provide clear go or no go input when technical readiness is incomplete or customer commitments create delivery risk.
• Work with vendors and partner engineering teams to define integration responsibilities, data handoffs, technical boundaries, support expectations, and escalation paths.
• Define how partner platforms fit into the NOV service wrapper for industrial data acquisition, data delivery, video, file workflows, operational communications, analytics, and customer endpoints.
• Translate partner capabilities and constraints into practical implementation plans for NOV teams and customer facing stakeholders.
• Track vendor readiness risks and make unresolved dependencies visible early.
• Help turn recurring partner integration patterns into reusable templates and documented standards.
• Support architecture and readiness for data movement from edge environments into cloud services, platform APIs, customer applications, partner systems, or external delivery endpoints.
• Validate end to end data flows, connectivity, access, authentication, security, monitoring, and operational handoff requirements across edge systems, networks, cloud services, APIs, partner platforms, and customer environments.
• Lead technical investigations and troubleshooting activities across edge, network, cloud, partner, and customer environments to identify and resolve integration, connectivity, deployment, and data quality issues before and during customer delivery.
• Partner with product, engineering, operations, implementation, support, SRE, cybersecurity, and customer facing teams to make deployments repeatable and supportable.
• Reduce one off delivery by documenting common integration patterns, technical assumptions, and deployment requirements.
• Drive technical improvements that reduce dual stack complexity, manual mapping, custom connector work, and one off deployment risk.
• Maintain integration documentation, readiness checklists, technical decision records, and reusable implementation templates.
• Define standards for what technical evidence is required before customer or partner execution begins.
• Turn lessons from PoCs, pilots, and partner deployments into improved architecture patterns, validation gates, and implementation guidance.
• Maintain reusable artifacts for customer reviews, internal readiness checks, partner onboarding, and steady state support.
• Leverage AI assisted tools to accelerate troubleshooting, architecture reviews, integration design, documentation, and solution validation while applying sound engineering judgment to validate results.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior