Data Integration Engineering Lead

About the role

We are building a team of trailblazers, who embody growth, impact, and excellence. The Enterprise Data Architect, Lead plays a crucial role in designing, implementing, and maintaining data integration solutions within our organization. This role collaborates with customers and cross-functional teams to ensure seamless data pipelines from customers’ systems.

Responsibilities

The key responsibilities of this role include:

• Source System Extraction: Independently extract data from industrial source systems including OSIsoft PI historians, SAP PM/EAM, Maximo, eMaint, lab/LIMS systems, and other CMMS/ERP platforms.
• Data Transformation and Pipeline Development: Design, build, and maintain data pipelines that clean, transform, and load extracted data into our reliability platform.
• Client Communication and Technical Leadership: Serve as the primary technical point of contact with customer IT teams for all data access and connectivity matters.
• Strategy and Team Building: Lead the enterprise data integration strategy and platform architecture across the organization.

Requirements

The following are required for this role:

• Hands-on experience extracting data from at least two of: OSIsoft PI, SAP PM/EAM, Maximo, eMaint, or similar industrial/operational systems.
• Experience in oil and gas, refining, chemicals, or heavy industry environments.
• Direct experience working with customer or client IT teams to negotiate and establish data access (firewall rules, VPN connectivity, service accounts, API credentials).
• SQL proficiency — specifically the ability to explore unfamiliar database schemas and write extraction queries with little or no documentation.
• Python for data extraction, transformation, and pipeline automation.
• Experience with cloud-based data integration (Azure Data Factory, Azure Functions, or comparable).
• Strong knowledge of data integration patterns, ETL/ELT, APIs, and messaging protocols (REST, SOAP, OPC).
• Demonstrated experience with enterprise database technologies and data modeling.
• Excellent communication skills — you’ll be the person answering detailed technical emails from client IT directors and leading discovery calls.

Qualifications

Preferred qualifications for this role include:

• Familiarity with reliability engineering concepts (RBI, CMMS workflows, asset hierarchy management, inspection data).
• Experience with Cognite Data Fusion (CDF) or similar industrial data platforms.
• Knowledge of PI Web API, PI SDK, or AF SDK for historian data extraction.
• Experience with OPC-UA/DA protocols for real-time industrial data.
• Background in data governance and compliance measures.
• Understanding of microservices architecture and containerization (Docker, Kubernetes).
• Experience with DevOps tools and practices (Azure DevOps, CI/CD pipelines).

Skills

The following skills are required for this role:

• Expertise in data integration tools and platforms (e.g., Azure Data Factory, Informatica, Talend).
• Proficiency in big data platforms (Hadoop, Spark, etc.) and analytics tools (Power BI, Tableau).
• Familiarity with DevOps tools and practices (e.g. Azure DevOps).