Data Architect (Mid Level)

Our client is a SaaS company providing pipeline integrity management software to oil and gas pipeline operators, spanning asset integrity, damage prevention, land management, and related risk workflows.

About the role

We're looking for a Data Architect to design the schema and data model powering Sentinel, a new AI-driven risk and asset integrity platform that unifies data across multiple products into one governed data platform. You will design a unified structure spanning asset integrity, damage prevention, and land and stakeholder management, capable of supporting probabilistic risk models that require dozens of precisely defined input attributes per pipeline segment. This is a hands-on design role: you will establish standards for data lineage, governance, and quality while working closely with the data engineering team to implement them. This is a skill-first role: hands-on experience with Databricks, Delta Lake, Unity Catalog, and medallion/lakehouse architecture matters far more than prior exposure to the oil and gas or pipeline integrity industry, which is a nice-to-have, not a requirement.

Responsibilities

• Design the schema and unified data model for the platform, spanning asset, inspection, incident, geospatial, and consequence data across multiple products.
• Apply medallion architecture patterns (Bronze, Silver, Gold) and define the semantic layer consumed by downstream models, reporting, and applications.
• Model the data required by probabilistic risk models, ensuring every required input attribute has a defined source, transformation path, and data-quality expectation.
• Design cross-product entity resolution so records from separate products reconcile to shared assets and entities.
• Define ingestion patterns for batch, streaming, and change-data-capture (CDC) sources, including schema evolution and slowly changing dimensions.
• Produce architecture documentation, diagrams, data dictionaries, and decision records that engineers can implement without ambiguity.
• Design the shared GIS layer as a first-class component of the data model, including pipeline centerlines, consequence-area polygons, right-of-way corridors, and parcel data.
• Model linear referencing and dynamic segmentation so risk results align with centerline geometry and can be aggregated across differing segmentations.
• Define data structures for inspection data, repair history, and external enrichment sources such as weather history, soil characteristics, and satellite-derived data.
• Define cataloging, classification, and metadata standards in Unity Catalog and establish expectations for lineage coverage across the data estate.
• Establish data-quality rules, validation gates, and profiling standards, including processes for quarantining and remediating failures.
• Define access-control patterns, including role-based and attribute-based access, tenant isolation, and appropriate handling of sensitive data.
• Work directly with data engineers to translate architectural designs into production pipelines and review implementations for conformance.
• Partner