Senior Manager Data Engineering and MLOps

Valvoline•Cincinnati, OH

1d•Onsite

About The Position

Valvoline Global Operations is seeking an experienced Senior Manager to lead its Data Engineering and MLOps functions. The role guides a team responsible for designing, building, and operationalizing an enterprise data platform that supports analytics, reporting, and machine learning across the organization. The leader will help deliver trusted, high-quality data and ensure that platforms are scalable, reliable, and aligned with business needs, with a focus on Databricks and integration with SAP systems. The position is based at Valvoline Global’s new Global Headquarters in Cincinnati, Ohio, scheduled to open in spring 2027. The role works in an office setting and requires travel of up to 10%.

Requirements

Bachelor’s or master’s degree in Computer Science, Engineering, Information Systems, Data Engineering, or a related field.
8–12+ years of experience in data engineering, data platforms, or analytics technology roles.
3–5+ years of leadership experience managing technical teams or driving enterprise-scale data initiatives.
Strong expertise in Databricks, including Spark/PySpark, Delta Lake, Unity Catalog, MLflow, and workflow orchestration.
Strong understanding of data engineering principles, ELT/ETL design, modern data warehousing, and cloud data architectures.
Ability to quickly learn and adopt SAP data technologies, including SAP BW/4HANA, SAP S/4HANA, and SAP Datasphere.
Experience with Azure, AWS, or GCP, including data storage, compute, orchestration, and DevOps tooling.
Proficiency in SQL and at least one programming language; Python is preferred.
Experience implementing CI/CD and DevOps practices for data and machine learning pipelines.
Strong communication, stakeholder management, and cross-functional leadership skills.

Nice To Haves

Hands-on experience with Databricks lakehouse architecture, including Delta Lake, Unity Catalog, MLflow, and advanced Spark optimization.
Practical experience with SAP Datasphere or other SAP data environments for modeling and integration.
Familiarity with SAP BW or SAP HANA data structures and extractors.
Understanding of data governance frameworks, access management, and data security best practices.
Experience supporting or enabling data science teams through feature engineering, model deployment, and MLOps tooling.
Exposure to real-time or streaming data integration frameworks.
Certifications in Databricks, SAP, or major cloud platforms.
Experience with BI tools such as Power BI or Tableau.

Responsibilities

Lead, mentor, and develop a high-performing Data Engineering and MLOps team supporting enterprise data and analytics initiatives.
Design, build, and optimize scalable, high-performance data pipelines and data products using Databricks, including PySpark, Delta Lake, and Unity Catalog.
Oversee integration of SAP BW/4HANA, SAP S/4HANA, and SAP Datasphere into cloud data platforms and analytics environments.
Partner with data architects, analysts, data scientists, and business stakeholders to gather requirements and deliver solutions that support strategic objectives.
Establish and manage MLOps frameworks for automated model training, deployment, monitoring, and lifecycle management using Databricks and MLflow.
Ensure and enforce data quality, metadata management, lineage tracking, and governance standards across the data ecosystem.
Implement monitoring, observability, and incident management processes to maintain platform reliability, performance, and uptime.
Evaluate emerging tools, technologies, and practices in data engineering, SAP integration, cloud architecture, and machine learning operations.
Create documentation, reusable frameworks, and standards to promote consistency, transparency, and scalability across data processes.
Collaborate with security, cloud, SAP, and enterprise architecture teams to ensure compliance, safety, and alignment with corporate technology strategy.