Your Opportunity as the Manager, Data Engineering - Enterprise Data Platform The Manager, Data Engineering is responsible for leading a team of Data Engineers focused on building and operating high-quality data pipelines within a modern cloud data platform. This role combines
people leadership, hands-on technical oversight, and operational excellence to deliver trusted, scalable, and efficient data solutions. As part of the Enterprise Data Platforms & Enablement team, this role partners closely with Cloud Engineering, Governance, Architecture, and business stakeholders to support a large-scale transformation from on-premise systems to cloud-native platforms. The Manager ensures that data engineering practices align with modern best practices, including Databricks-based development, medallion architecture (bronze/silver/gold layers), and automated data ingestion frameworks (e.g., Fivetran).
Location: Orrville, OH (Close proximity to Cleveland/Akron)
Work Arrangements: Hybrid - onsite a minimum of 9 days a month primarily during core weeks as determined by the Company; maybe more as business need requires
In this role you will: - Team Leadership & Delivery
- Lead, coach, and develop a team of Data Engineers, fostering strong technical skills and ownership
- Set clear priorities, manage workload, and ensure timely delivery of data engineering initiatives
- Establish engineering standards, code quality expectations, and best practices across the team
- Partner with stakeholders to translate business needs into scalable data solutions
- Data Pipeline Engineering
- Oversee the design, development, and operation of data pipelines built in Databricks
- Ensure pipelines are scalable, reliable, and aligned to medallion architecture standards (bronze, silver, gold)
- Guide implementation of ingestion frameworks using tools like Fivetran and custom ingestion patterns
- Drive consistent development patterns for batch and near real-time data pipelines
- Platform & Architecture
- Provide technical leadership for the Databricks platform, including workspace, jobs, clusters, and performance optimization
- Collaborate with Cloud Engineering to ensure seamless integration with AWS services (e.g., S3)
- Ensure alignment with enterprise architecture, including data modeling, partitioning strategies, and storage optimization
- Optimize compute usage for performance and cost efficiency
- Data Quality, Governance & Reliability
- Establish and enforce data quality standards, including testing, validation, and monitoring frameworks
- Ensure robust observability across pipelines (monitoring, alerting, lineage visibility)
- Partner with Governance teams to support metadata management and lineage through tools like Atlan
- Enforce security, compliance, and data access standards across all data engineering assets
- Operations & Continuous Improvement
- Own production support processes, including incident management, root cause analysis, and prevention
- Establish proactive monitoring and health checks for pipelines and platform performance
- Drive continuous improvement in automation, CI/CD, and release management practices
- Support and lead data migration efforts from legacy on-prem systems to cloud platforms
What we are looking for: Minimum Requirements:
- Bachelor's Degree or equivalent experience
- 7+ years of experience in data engineering or data platform roles
- 3+ years of experience leading and developing technical teams
- Experience operating in modern cloud data environments (Databricks, data lakes, or lakehouse platforms)
- Proven experience delivering enterprise-scale data pipelines and platforms
- Experience supporting cloud migration or modernization initiatives
- Strong expertise in Databricks (notebooks, jobs, cluster management)
- Proficiency in Python and PySpark for distributed data processing
- Advanced SQL skills and experience working with large-scale datasets
- Experience designing and operating cloud-based data platforms (AWS preferred)
- Experience with data ingestion tools (e.g., Fivetran or similar)
- Deep understanding of data modeling and medallion architecture patterns
Additional skills and experience that we think would make someone successful in this role (not required):
- AWS services such as S3, IAM, and data storage architectures
- Data governance tools such as Atlan or similar
- Reporting and visualization tools such as Tableau
- CI/CD tools and automation frameworks
- Monitoring and observability tools for data platforms
The Right Place for You We are bold, kind, strive to do the right thing, we play to win, and we believe in a strong community that thrives together. Our culture is rooted in our Basic Beliefs, and we believe in supporting every employee by meeting their physical, emotional, and financial needs.
Stay connected with us on LinkedIn
We're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, genetic information, age, national origin, disability status or protected veteran status.
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