{"id":1559729,"url":"https://alion.io/job/global-partners-senior-director-data-engineering","title":"Senior Director, Data Engineering","company":{"id":2042557,"name":"Global Partners","domain":"globalp.com","url":"https://alion.io/company/globalp","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":null},"role":"Leadership","role_family":"Leadership","seniority":"head","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Newton, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":182300,"max":291500,"currency":"USD","period":"year","gross":null,"usd_annual":291500},"salary_estimate":null,"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"Dagster","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Embeddings","optional":false},{"name":"Feature Store","optional":false},{"name":"FinOps","optional":false},{"name":"Fivetran","optional":false},{"name":"Git","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Looker","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Shift-Left","optional":false},{"name":"Shift-Left Security","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-09-09T06:27:06Z","employer_posted_date":"2026-09-09","last_verified_at":"2026-10-13T22:35:10Z","board_verified":true,"closed_at":null,"days_open":34,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":34},"description":"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.\nAt 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.\nThe 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.\nYour Role, Your Impact\nStrategy & Platform Direction\nDefine, 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.\nSet 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.\nLead 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).\nEstablish data engineering as a measurable driver of company performance - uptime, time-to-insight, decision quality, and operating margin contribution.\nAgentic & AI-Assisted Engineering\nChampion 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.\nBuild 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.\nPartner 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.\nEstablish 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.\nData Platform, Quality & Governance\nOwn 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.\nLead the engineering side of MDM, partnering with the implementation and downstream consumers to ensure governed, conformed dimensions across the enterprise.\nChampion robust data governance - security, privacy, access control, lineage, and compliance - and embed these as automated, shift-left checks rather than after-the-fact reviews.\nLead initiatives to modernize core data systems for real-time and near-real-time business operations across terminals, retail, and supply/trading.\nOwn platform FinOps: visibility, attribution, and continuous optimization of data platform compute, storage, and AI/inference spend.\nOrganization & Talent\nLead 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.\nDevelop strategies for building world-class data engineering teams - fostering a culture of innovation, collaboration, curiosity, ownership, and data-driven decision-making.\nOversee team operations and engineering practice: agile delivery, sprint planning, code review, CI/CD, testing, on-call, postmortems, and continuous improvement of the SDLC.\nMentor senior engineers and engineering managers; build a deliberate pipeline of technical leaders fluent in both modern data stack and AI-augmented development.\nCross-Functional Leadership\nEstablish cross-functional alliances to drive data and AI innovation in partnership with Data Science/ML, Central Analytics, Technical Product Management, IT, Cybersecurity, and the business units.\nLead the data engineering aspects of major corporate initiatives and digital transformations, including the multi-year AI strategy and the federated DAI buildout.\nCollaborate with stakeholders across Operations, Retail, Supply & Trading, Finance, and HR to translate complex business needs into data products and technical requirements with clear ROI.\nBuild strong, influential partnerships across the organization, driving adoption of the enterprise data strategy and the AI-assisted ways of working.\nEffectively communicate platform strategy, progress, risks, and impact to diverse stakeholders - including the COO, CPO, CEO, and Board-level audiences when called on.\nQualifications\nExperience\n12+ years of experience in Data Engineering, Analytics Engineering, or Data Platform leadership, with a minimum of 7 years in senior management roles.\nAt least 6 years leading, mentoring, and developing technical staff in a dynamic, innovative environment, including managing managers.\nBachelor’s or Master’s degree in a quantitative field such as Computer Science, Mathematics, Statistics, Engineering, Physics, or Economics.\nDemonstrated experience operating in a federated (hub-and-spoke) data organization, supporting both centrally-owned platforms and embedded business-unit analytics teams.\nModern Data Stack & Platform\nExpert-level technical knowledge of the modern data stack, with deep proficiency in Snowflake, dbt, Dagster (or Airflow), and a cloud lakehouse pattern; working knowledge of Databricks/SageMaker, Fivetran, Hightouch/Census, DataHub (or comparable catalog/observability), Tableau, and Git-based workflows.\nStrong fluency with cloud infrastructure (AWS preferred), infrastructure-as-code, containerization, and modern CI/CD.\nProven track record of designing and operating production data systems with formal data contracts, SLAs, lineage, and observability.\nHands-on understanding of streaming and near-real-time architectures (e.g., Kafka, Snowflake Dynamic Tables, change data capture) and when to apply them.\nDemonstrated ability to manage cloud data platform cost (FinOps): attribution, governance, and continuous optimization of Snowflake and adjacent compute spend.\nAI / Agentic Engineering\nDemonstrated experience integrating AI-assisted and agentic development tooling (e.g., Claude Code, Cursor, MCP servers, shared skills/tools repositories) into the day-to-day workflow of engineering and analytics teams.\nPractical understanding of how to design, evaluate, and govern LLM- and agent-based features in production - including evals, human-in-the-loop patterns, prompt/skill versioning, and observability.\nFamiliarity with the data infrastructure that supports AI/ML products: feature stores, vector databases, RAG retrieval pipelines, embeddings management, and model/agent monitoring.\nComfortable setting standards for safe and effective use of AI in regulated, operationally critical environments.\nEngineering & Delivery Practice\nExtensive experience with software engineering best practices and agile delivery (sprint planning, code review, testing, CI/CD, on-call, postmortems).\nSubstantial experience partnering with product management - stakeholder management, roadmap negotiation, ROI reasoning, and synthesizing diverse viewpoints into a coherent plan.\nProficiency in Python and SQL; comfortable reading and reviewing code across the team’s primary languages.\nFamiliarity with data analysis and BI tooling (Tableau, Looker, or equivalent) sufficient to partner credibly with analytics consumers.\nWorking understanding of statistical methods and ML fundamentals; able to engage substantively with data science partners.\nLeadership & Communication\nA passion for data quality, systems design, and developer experience, coupled with curiosity about how teams and systems succeed and grow.\nStrong leadership and interpersonal skills; capable of building and maintaining trusted relationships across departments and fostering a collaborative, empowering management style.\nExcellent written and verbal communication, with the ability to articulate complex technical and AI strategies to executive and Board-level audiences.\nComfort operating with ambiguity and leading through change, including standing up new teams, capabilities, and ways of working.\nBachelor's Degree Computer Science, Engineering or related quantitative field\nPay Range$182,300.00 - $291,500.00The pay range for this position is outlined above. The final amount offered at the start of employment is determined based on factors including, but not limited to, experience level, knowledge, skills, abilities and geographic location, and the Company reserves the right to modify base salary at any time, including for reasons related to individual performance, Company or individual department/team performance and market factors.\nOur Commitments to You\nCompetitive Pay - We offer competitive salaries and opportunities for growth within.\nHealth & Wellness - Medical, Dental, Visions and Life Insurance. Along with additional wellness support.\nThe Road Ahead - We offer 401k and a match component. We also provide tuition reimbursement; this benefit is offered after 6 months of service.\nProfessional Development - We value lifelong learning and have many internal development programs and access to other on-demand learning for continued career growth.\nThese commitments are offered to employees in permanent roles, as part of our support for long-term growth and success\nWhat to Expect From the Hiring Process\nWe value passion and potential. Please apply if you’re qualified and interested-we’d love to hear from you.\nA member of our Talent Acquisition team will review your application and may connect you with the hiring manager if your experience is a strong match.\nInterviews are conducted virtually and in person, depending on the role. We’ll provide more details about next steps if selected to move forward.\nGlobal Partners LP is an equal opportunity employer. We foster a company culture where ideas from all people help us grow, move and thrive. We embrace the diversity of all applicants and do not discriminate against race, color, religion, sex, age, national origin, sexual orientation, gender identity, disability, protected veteran status or any other basis prohibited by federal, state or local law. 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