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Job Description

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. The expertise for this role will contribute to the organization’s overall strategy and architecture for data acquisition.

Job Duties

• Source System Extraction (This Is the Core of the Role)

• Independently extract data from industrial source systems including OSIsoft PI historians, SAP PM/EAM, Maximo, eMaint, lab/LIMS systems, and other CMMS/ERP platforms.
• Navigate customer IT environments to establish connectivity — VPNs, service accounts, firewall rules, read-only database access — often with limited or no documentation.
• Reverse-engineer undocumented or poorly documented source schemas to identify the right data for integration.
• Build and own the extraction layer: connectors, API calls, direct database queries, file-based ingestion from heterogeneous client environments.
• Handle the reality that every customer’s data is messy in a different way — inconsistent tag naming, mismatched equipment IDs, unmaintained asset hierarchies.

• Data Transformation and Pipeline Development

• Design, build, and maintain data pipelines that clean, transform, and load extracted data into our reliability platform.
• Develop integration architecture and blueprints tailored to each customer’s source system landscape.
• Implement data quality checks, reconciliation processes, and monitoring to ensure ongoing accuracy.
• Build and maintain master data mapping strategies — including change management processes as clients execute MOCs, add equipment, or decommission assets.
• Own pipeline monitoring, alerting, and uptime SLAs for all production data extraction and integration systems. These are live production pipelines serving customers — when extraction fails, you are responsible for detecting the failure, diagnosing the root cause, and restoring the data flow within SLA.

• Client Communication and Technical Leadership

• Serve as the primary technical point of contact with customer IT teams for all data access and connectivity matters.
• Respond to detailed technical inquiries from client IT leadership (architecture questions, data mapping strategies, security concerns) with clarity and confidence.
• Lead discovery sessions with customers to understand their source systems, data flows, and integration requirements.
• Create and maintain architecture documentation, integration runbooks, and data dictionaries for each client engagement.
• Provide technical guidance and mentorship to team members and drive knowledge sharing across the data engineering team.
• Manage integration project plans, timelines, and deliverables across multiple concurrent client engagements. Drive accountability on milestones, coordinate dependencies with client IT teams, and ensure integrations are completed on schedule.

• Strategy and Team Building

• Lead the enterprise data integration strategy and platform architecture across the organization.
• Provide new ideas and approaches to the CTO and enterprise architecture team on data acquisition and integration best practices.
• Drive recruitment to build and grow a high-performing data engineering team.
• Continuously evaluate and adopt emerging data technologies and practices.

Accountabilities/Results/Success for this role   

• Successful design and deployment of scalable and secure data architectures and data pipelines.
• Enhanced data quality, efficiency, and accessibility across the organization.
• Effective execution of data integration projects, demonstrating strong project management skills and consistent delivery on time and within scope.
• Continuous improvement and adoption of emerging data technologies and practices.
• Creation of innovative, customer-focused data solutions that set the organization apart and add measurable value.

Measures

Percentage of projects delivered on time: 80%

Team utilization: 80%

Data Solutions: 3

Production pipeline uptime: 99.5%

Required Qualifications/Skills/Competencies

• Hands-on experience extracting data from at least two of: OSIsoft PI, SAP PM/EAM, Maximo, eMaint, or similar industrial/operational systems. This is non-negotiable.
• 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

Preferred Qualifications

• 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

Equipment and Software Knowledge

• 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).

Direct Reports

Data Engineers will report to this role