Data Integration Engineering Lead

Job Summary This•Pasadena, TX

About The Position

This role is responsible for figuring out how to extract data from diverse customer environments, including industrial source systems like OSIsoft PI historians, SAP PM systems, legacy CMMS, and lab systems. The individual will work directly with customer IT teams to establish connectivity, understand source schemas, and build the extraction layer for the company's reliability platform. This involves navigating IT security, reverse-engineering undocumented schemas, and handling messy, inconsistent data. The role also includes designing and building data pipelines for cleaning, transforming, and loading data, developing integration architectures, implementing data quality checks, and managing master data mapping. Pipeline monitoring, alerting, and ensuring uptime SLAs are critical. Additionally, the position serves as the primary technical point of contact for customer IT teams, leading discovery sessions, creating documentation, and providing technical guidance and mentorship. The lead will also drive the enterprise data integration strategy, contribute to best practices, lead recruitment efforts, and evaluate new data technologies.

Requirements

Hands-on experience extracting data from at least two of: OSIsoft PI, SAP PM/EAM, Maximo, eMaint, or similar industrial/operational systems.
Experience working with or for heavy process/industrial industries; refining, chemical/petrochemical, manufacturing, mining, water/wastewater, etc.
Must understand maintenance data.
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.

Responsibilities

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.
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.
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.
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.