OT Integration Engineer

Essential Duties and Responsibilities:

As an OT Integration Engineer at Kinetik, you design, build, and support the pipelines, APIs, SQL models, data products, and integration services that help operational and business data move reliably across the organization. You play a critical role that enables Kinetik to shape its large collection of operational and business data into insights that empower our employees, improve safety, and streamline operations.

Data pipeline and integration engineering

Construct and support real-time and batch data pipelines connecting SCADA platforms, historians, databases, APIs, business systems, and enterprise analytics environments.
Establish and promote reliable integration patterns for operational data movement across OT, DMZ, cloud, and enterprise environments.
Deploy, secure, and maintain industrial MQTT / Sparkplug B broker infrastructure across OT, DMZ, and analytics network zones, including edge brokers near source systems, broker bridging and aggregation into enterprise-level brokers, and store-and-forward resilience.
Organize and simplify integrations involving SCADA, historian, FlowCal, SQL Server, Ignition, AVEVA / Wonderware, MQTT / Sparkplug B, OPC UA, REST APIs, Solace, HighByte, and new business systems.

API, SQL, and data product development

Develop APIs, services, SQL models, views, stored procedures, and reusable data access patterns that expose relevant OT data to business and analytics consumers.
Define and maintain data contracts, schemas, naming standards, interface patterns, and documentation for operational data products.

Reliability, monitoring, and troubleshooting

Implement monitoring, logging, alerting, retry behavior, fault handling, and recoverability patterns for production data pipelines and integration services.
Investigate data pipeline failures, latency issues, missing data, schema changes, stale data, duplicate records, and unexpected data movement behavior.
Distinguish integration issues from source-system issues or downstream model/tool issues and assist primary stewards with corrections.

Software engineering and change control

Reduce dependence on manual file handling, duplicated queries, spreadsheet-driven workflows, unmanaged scripts, and fragile point-to-point interfaces.
Apply source control, modular design, testing, versioning, peer review, CI/CD, and maintainable development practices where appropriate.
Support controlled change management for schemas, APIs, SQL objects, data pipeline logic, and integration interfaces.

Team support and documentation

Coordinate with analytics team members to hunt down problems in the OT Data Ecosystem.
Maintain documentation for supported systems.

Collaboration and communication expectations

Assist OT Systems Specialists to ensure data pipeline assumptions match field, SCADA, historian, FlowCal, and measurement-system realities.
Assist AI Analytics Engineers to understand data requirements for forecasting, optimization, predictive maintenance, RAG systems, AI assistants, and decision-support tools.
Coordinate with IT / Infrastructure, Operations, Measurement, Commercial, Environmental, Engineering, and other stakeholders during integration design, troubleshooting, and support.
Support other OT Analytics team members during workload spikes, incidents, commissioning efforts, dashboard/tool development, or high-priority projects, while preserving the primary ownership boundaries defined for each role.
Communicate data flow, system dependencies, latency, availability, failure modes, and technical tradeoffs clearly to technical and non-technical audiences.
Preserve clear ownership of data pipelines, APIs, SQL models, schemas, and data products while supporting the broader OT data value chain.
All other duties as assigned.

Education and/or Work Experience Requirements:
Required:

Bachelor’s degree in computer science, engineering, information systems, or a related technical field;equivalent industry experience will be considered.
5+ years of relevant experience in data, integration, software engineering, industrial automation, OT/IT analytics, or related technical work.
Strong SQL and relational database skills, including data validation, troubleshooting, reusable data access patterns, views, stored procedures, and timestamp-based analysis.
Experience designing, supporting, and troubleshooting production data pipelines, APIs, SQL models, integration services, scripts, or automated workflows.
Working knowledge of structured data formats, APIs, data movement patterns, data contracts, schema discipline, and secure system-to-system integration.
Experience supporting production systems, monitoring, logging, alerting, fault handling, recovery, and troubleshooting.
Experience with MQTT / Sparkplug B, OPC UA, REST APIs, historian integrations, SQL Server integrations, event streaming, or similar technologies.

Preferred:

Experience with, and preferably experience deploying and administering, MQTT brokers (such as Solace, HiveMQ, EMQX, or Chariot), including broker bridging or aggregation across network zones, topic namespace design, and Sparkplug B concepts such as birth/death certificates and metric metadata.
Experience with HighByte or similar industrial data integration platforms.
Experience with Python, PowerShell, containerization, Windows and Linux environments, source control, testing, peer review, CI/CD, or related maintainable development practices.
Experience in oil and gas, midstream, utilities, manufacturing, or another industrial environment.
Experience with AVEVA Wonderware, AppServer, AVEVA Historian, Ignition (including MQTT Engine / MQTT Transmission modules), FlowCal, Autosol ACM, TopServer / Kepware, or related OT and measurement systems.
Familiarity with Databricks, Palantir Foundry, Power BI, Snowflake, or similar analytics and data platforms.
Understanding of OT cybersecurity basics, industrial protocols, and segmented network environments.
Experience replacing point-to-point interfaces or replicated-historian architectures with publish/subscribe data movement, including preserving tag metadata and data quality context through the pipeline.

Working Conditions:

Will be working in an office environment with prolonged periods of sitting and working on a computer.
Will work outdoors in adverse or extreme weather conditions on occasion
Will be required to frequently drive to other field facilities within their assigned region.
Primarily office-based, with most work performed using computers, databases, development tools, analytics platforms, and remote system access
Regular collaboration with Executive, Operations, Measurement, Commercial, Engineering, IT, and OT department members to understand business needs and validate analytics solutions
Limited field travel required, typically a few site visits per year, with occasional additional travel to operational sites, compressor stations, or field locations
May occasionally support urgent analytics, reporting, model, or data-related issues that affect operational or commercial decision-making

Physical Requirements:

Ability to safely and successfully perform the essential job functions consistent with the ADA, FMLA and other federal, state and local standards, including meeting qualitative and/or quantitative productivity standards.
Ability to maintain regular, punctual attendance consistent with the ADA, FMLA and other federal, state and local standards
Ability to work effectively in all working conditions noted above.
Must be able to communicate clearly and professionally in person, over the telephone, and in virtual communication settings with technical and non-technical personnel.
Ability to sit for extended periods while working at a computer and performing remote system configuration.
Ability to occasionally travel to field locations, compressor stations, and other operational sites and safely navigate industrial environments.
Must be able and willing to work extended hours and respond to urgent operational issues as business needs require.
Ability to lift standard computer equipment, laptops, monitors, and related materials as needed.