Manager, Data Engineering

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.

• Lead, mentor, and develop a small team of data professionals (Data Engineer, Junior DBA, BI developers), establishing clear goals, career development plans, and engineering best practices.
• Define the short- and long‑term data engineering roadmap aligned to business priorities and CIO strategy.
• Own the enterprise data architecture across on‑prem and cloud environments (Microsoft SQL Server, AWS/Azure/GCP), ensuring reliability, scalability, and security.
• 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 initiatives.
• Maintain architecture documentation and ensure the environment evolves with business needs.

• Ensure 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 manner.
• Support team as they architect, build, and operationalize scalable ETL/ELT pipelines using Python, off‑the‑shelf ETL tools, and other orchestration tools.
• Set standards for CI/CD, automated testing, monitoring, and alerting for data pipelines and database deployments.
• Establish and enforce backup, archiving, retention, and disaster recovery strategies for databases and datasets.
• Optimize databases and queries for reliability, performance, and cost efficiency — including indexing, partitioning, and tuning strategies.

• Implement and govern data quality, metadata management, lineage, and cataloging practices.
• Define and enforce data access controls, encryption, and security policies to meet compliance and internal requirements.
• Create SLAs and runbooks for incident response and data platform support.
• Leads AI forward problem solving methodologies to standardize data, accelerate change, and collaborate across business units.

• Collaborate closely with Software Development, Program Management, and business stakeholders to integrate new applications and third‑party data sources.
• 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 solutions.

• Lead POCs and production rollouts of AI‑driven automation and integrations (ML/AI pipelines, process automation), align solutions with future‑state architecture and process transformation.
• 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 satisfaction.
• Create an environment where PTL Human Assets can be creative, make good decisions, and move fluidly as fuel markets and strategies evolve.
• Evaluate, onboard, and manage third‑party data tools and cloud services.
• Monitor and manage cloud and platform costs; recommend optimizations and capacity planning.

• Special projects as requested.
• Perform other duties as assigned.

• Industry experience in downstream fuel logistics or comparable industry knowledge.
• Deep expertise in SQL and relational database design and performance tuning (Microsoft SQL Server required).
• Strong Python development skills and proven experience building ETL/ELT pipelines.
• Experience with orchestration tools (e.g., Apache…