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Manager, Data Engineering
The J.M. Smucker Co.Manager, Data Engineering responsible for building and operating data pipelines in cloud data platform. Leading a team focused on modern data engineering practices and cloud solutions.
Tech Stack
Tools & technologiesAWSCloudPySparkPythonSQL
About the role
Key responsibilities & impact- 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
- 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
- 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
- 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
- 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
Requirements
What you’ll need- 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
Benefits
Comp & perks- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonPySparkSQLDatabricksdata pipelinesdata modelingmedallion architecturedata ingestioncloud migrationCI/CD
Soft Skills
leadershipcoachingcommunicationprioritizationcollaborationproblem-solvingtechnical guidanceteam developmentincident managementcontinuous improvement
Certifications
Bachelor’s Degree