Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Global Partners
Join Global Partners as Senior Director of Data Engineering to lead the architecture, development, and optimization of our enterprise data platform. This role drives the design and implementation of modern, AI-native data infrastructure that powers analytics, operations, real-time decisioning, and digital transformation across our energy value chain — terminals, retail convenience stores, fuel marketing, and supply and trading. It is a pivotal role in enabling data-driven decision-making and AI-enabled innovation across the organization. Your mission extends beyond conventional data engineering. You will lead a team that operates at the modern data stack — Snowflake, dbt, Dagster, DataHub, and a maturing portfolio of streaming, ML, and agentic capabilities — while embedding agentic development practices (Claude Code, Cursor, MCP-based tooling, AI-assisted code review and data quality) as the default way our engineers, analytics engineers, and embedded BI teams build and ship. You will translate complex business questions into durable technical strategy, set the platform direction that the central Data, Analytics & Insights (DAI) organization and embedded BU analytics teams build on, and serve as the senior technical voice partnering with Data Science/ML, Central Analytics, Technical Product Management, IT, and business leadership. This role is tailor-made for a leader who finds their passion at the intersection of data, AI, and operational impact, and who wants to help define what a federate data organization looks like at a Fortune 500 energy company.
At Global Partners, business starts with people. Since 1933, we’ve believed in taking care of our customers, our guests, our communities, and each other—and that belief continues to guide us.
The Global Spirit is the cornerstone of our commitment to success. As a Fortune 500 company with 90+ years of experience, we’re proud to fuel communities—responsibly and sustainably. We show up every day with grit, passion, and purpose—anticipating needs, building lasting relationships, and creating shared value.
Your Role, Your Impact
Strategy & Platform Direction
- Define, execute, and evolve a forward-thinking enterprise data and platform strategy aligned with Global Partners’ long-term objectives, ensuring scalable, reliable, governed, and cost-aware data solutions.
- Set and own the multi-year roadmap for the core data platform (Snowflake, dbt, Dagster, DataHub, Tableau, and adjacent ML/AI infrastructure), including a credible path to streaming, real-time activation, data-mesh archiecture and AI/ML enablement.
- Lead data engineering strategy for expansion into new business areas, M&A integrations, and adjacent revenue opportunities (e.g., new fuel products, retail loyalty, mobility, sustainability reporting).
- Establish data engineering as a measurable driver of company performance — uptime, time-to-insight, decision quality, and operating margin contribution.
Agentic & AI-Assisted Engineering
- Champion and operationalize agentic development as the default way the team builds: standardize development conventions, shared skills/tools repositories, and MCP-based integrations across Data Engineering, DSML, and embedded teams.
- Build and govern the internal AI tooling layer for data work — agent-assisted development, automated lineage and documentation, AI-driven code review, agentic data quality and incident triage, and natural-language interfaces to the warehouse.
- Partner with the DSML team to provide the data and platform foundations for AI/ML products, including feature store, vector store, RAG retrieval infrastructure, evaluation tooling, and model/agent observability.
- Establish the engineering guardrails for safe, reliable use of LLMs and agents in production data workflows — including human-in-the-loop patterns, evals, prompt and skill versioning, and audit trails.
Data Platform, Quality & Governance
- Own the integrity of the dbt layer conventions (RAW → CUR → BTR → APP), data contracts, SLAs, and the Single Source of Truth (SSOT) discipline that downstream BUs depend on.
- Lead the engineering side of MDM, partnering with the implementation and downstream consumers to ensure governed, conformed dimensions across the enterprise.
- Champion robust data governance — security, privacy, access control, lineage, and compliance — and embed these as automated, shift-left checks rather than after-the-fact reviews.
- Lead initiatives to modernize core data systems for real-time and near-real-time business operations across terminals, retail, and supply/trading.
- Own platform FinOps: visibility, attribution, and continuous optimization of data platform compute, storage, and AI/inference spend.
Organization & Talent
- Lead and grow the central Data Engineering function within the federated DAI organization, supporting both centrally-owned platforms and the embedded BI teams across business units.
- Develop strategies for building world-class data engineerin
Source: Global Partners careers