Manager, Data Engineering

Position Summary:

We are seeking a strategic, hands-on Manager, Data Engineering to own and evolve our enterprise data platform and analytics ecosystem. Reporting to the CIO, this role is responsible for defining the data engineering roadmap, leading a small cross-functional team, and delivering robust, scalable, secure data capabilities that enable self-service analytics, operational reporting, and AI/automation initiatives.

The Manager, Data Engineering will be both a technical leader and people manager. This is a hands-on data engineering role. As a leader you will be mentoring individual contributors, partnering with business leaders and vendors for success, and shaping data strategies throughout the business

.
Essential Responsibilitie

s:Leadership & Strate

• gyLead, mentor, and develop a small team of data professionals (Data Engineer, Junior DBA, BI developers), establishing clear goals, career development plans, and engineering best practice
• s.Define the short- and long-term data engineering roadmap aligned to business priorities and CIO strateg

y.Architecture & Platfo

• rmOwn the enterprise data architecture across on-prem and cloud environments (Microsoft SQL Server, AWS/Azure/GCP), ensuring reliability, scalability, and securit
• y.Design and oversee implementation of a modern data platform (data lake / lakehouse / data warehouse patterns as appropriate) and data modeling standards to support analytics, data automation/integration and AI initiative
• s.Maintain architecture documentation and ensure the environment evolves with business need

s.Data Engineering & Operatio

• nsEnsure key data required to support sales, supply, and operations is procured, maintained, and managed to provide the business with necessary functional information in a timely manne
• r.Support team as they architect, build, and operationalize scalable ETL/ELT pipelines using Python, off-the-shelf ETL tools, and other orchestration tool
• s.Set standards for CI/CD, automated testing, monitoring, and alerting for data pipelines and database deployment
• s.Establish and enforce backup, archiving, retention, and disaster recovery strategies for databases and dataset
• s.Optimize databases and queries for reliability, performance, and cost efficiency — including indexing, partitioning, and tuning strategie

s.Governance, Security & Quali

• tyImplement and govern data quality, metadata management, lineage, and cataloging practice
• s.Define and enforce data access controls, encryption, and security policies to meet compliance and internal requirement
• s.Create SLAs and runbooks for incident response and data platform suppor
• t.Leads AI forward problem solving methodologies to standardize data, accelerate change, and collaborate across business unit

s.Cross-Functional Partnersh

• ipCollaborate closely with Software Development, Program Management, and business stakeholders to integrate new applications and third-party data source
• s.Provide thought leadership and suggest solutions as teams are moving toward future state operations. Promote unified data sets, intelligence layers, and enterprise readiness, and other nimble and creative adaptive solution

s.AI & Automati

• onLead POCs and production rollouts of AI-driven automation and integrations (ML/AI pipelines, process automation), align solutions with future-state architecture and process transformatio
• n.Create and protect PTL Data Assets that can be used to drive value. Participate in governance, compliance, monitoring, and security initiatives to protect data assets and promote customer satisfactio
• n.Create an environment where PTL Human Assets can be creative, make good decisions, and move fluidly as fuel markets and strategies evolv

e.Vendor & Cost Manageme

• ntEvaluate, onboard, and manage third-party data tools and cloud service
• s.Monitor and manage cloud and platform costs; recommend optimizations and capacity plannin

g.
Other Functio

• ns:Special projects as request
• ed.Perform other duties as assign

ed.
Minimum Requireme

nts:Requ

• iredIndustry experience in downstream fuel logistics or comparable industry knowle
• dge.Deep expertise in SQL and relational database design and performance tuning (Microsoft SQL Server requir
• ed).Strong Python development skills and proven experience building ETL/ELT pipeli
• nes.Experience with orchestration tools (e.g., Apache Airflow) and CI/CD for data workfl
• ows.Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and a working knowledge of hybrid cloud/on-prem environme
• nts.Demonstrated ability to lead technical teams, mentor engineers, and manage cross-functional initiati
• ves.Excellent communication skills and experience translating complex technical ideas to non-technical stakehold

ers.Prefe

• rred8 years of professional experience in data engineering, data architecture, or related roles, with at least 3 years in a leadership or technical lead capacity, highly prefer
• red.Familiarity with AI/ML technologies, MLOps, and integrating AI into automation and data pipeli
• nes.Exposure to containerization (Docker), orchestration (Kubernetes), infrastructure as code (Terraform), and DevOps practi
• ces.Cloud or data engineering certifications (AWS/Azure/GCP/Data Engineering) a p

lus.
Educa

• tion:Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related f

ield.
What Success Looks Like (First 6-12 Mo

• nths):A documented, prioritized data engineering roadmap aligned with CIO and business objec
• tives.Stable, monitored ETL pipelines with CI/CD, automated tests, and clear runbooks; measurable improvements in reliability and pipeline
• SLAs.Clear data governance framework, including access controls, quality checks, and documentation of enterprise dat
• asets.A growing and engaged data team with established mentorship and development r
• hythm.Tangible progress on AI/automation pilots and integrated data solutions that begin to show business

value.
Working Cond

• itions:Must be able to occasionally lift as much as ten (1
• 0) lbs.May be required to sit and review information on a computer screen for long periods