Director, Data Architecture

Phillips 66 & YOU - Together we can fuel the future   As the Director, Data Architecture  you will be the founding architect for the commercial knowledge layer. It is a principal-level role that owns the semantic and data architecture unifying market, operational, and trading data into governed, reusable data products that traders and data scientists can trust. The value here is the trading-specific model of the data, not the infrastructure beneath it: you will partner with Enterprise Analytics' Data-as-a-Service platform and build on it rather than rebuild it.   Phillips 66 Commercial is standing up its data science and analytics capability, and this is a rare chance to design its data architecture from the ground up and own it end to end. Traders, market analysts, and data scientists are ready to move faster; what they need is a unified knowledge layer they can all trust — one canonical, point-in-time-correct model of the entities that drive trading: grades, curves, cargoes, vessels, locations, counterparties, and assets.   What You’ll Do

Design the commercial semantic layer and ontology: canonical entities, relationships, and business definitions shared across desks. Establish golden-source master and reference data for commodities (instruments, curves, grades, locations, counterparties, assets) with clear ownership and stewardship. Define data products and contracts (schema, SLA, quality, lineage) on top of the enterprise medallion and Gold layer, so consumers get documented, trusted datasets. Build point-in-time and bitemporal correctness into the foundation so research and backtests are reproducible and free of lookahead bias. Drive entity resolution across messy physical and financial data (the same vessel, cargo, or counterparty across sources). Set data modeling, quality, and governance standards, and push validation upstream instead of leaving it to strategists. Partner with the enterprise data team as the delivery engine, while serving traders, market analysts, and data scientists as the primary consumers, so one knowledge layer feeds both human decisions and ML/GenAI.

What success looks like

One trusted, governed source of truth for commercial data, so teams stop rebuilding and reconciling Traders, analysts and data scientists consume documented data products with known lineage, freshness, and quality Research is reproducible: point-in-time correct, auditable, and free of lookahead The semantic layer measurably accelerates new desk use cases and the trader interface Duplicate knowledge systems retired against a single shared model

What You’ll Bring – Required

Legally authorized to work in the job posting country Bachelor’s degree in Information Technology, Computer Science, Business, Engineering, or a related field 7 or more years of experience as a principal-level data architect designing semantic layers, canonical data models, or master/reference data for a data-intensive business Advanced proficiency in data modeling, ontologies, and data-product and data-contract design Advanced proficiency in point-in-time and bitemporal data and why it matters for trustworthy analytics and research Travel up to 5% of the time

What Makes You Stand Out – Preferred

Track record building golden-source reference data and entity resolution across messy, multi-source data Experience with modern lakehouse and governance stacks (e.g., Databricks/Unity Catalog, medallion architecture, catalog and lineage tooling) Experience with commodities, energy, or financial trading data (curves, instruments, positions, physical logistics) Background architecting data for both BI/human consumption and ML/quant research Experience standing up data governance and stewardship operating models Familiarity with knowledge graphs and semantic or natural-language query enablement Hands-on Databricks and Unity Catalog experience Ability to set standards and influence across