Senior Data Engineer
On-siteAnn Arbor, Michigan, United States
Job Summary
Design, build, and optimize scalable data pipelines and reusable engineering frameworks using Azure Data Factory, Databricks, Spark, and streaming technologies. Lead ingestion, transformation, and data product frameworks supporting enterprise-scale structured, semi-structured, and unstructured data while implementing automation for reliability and observability. Drive future-state data architecture and cloud migration patterns, optimizing workflows for performance and cost through Delta Lake, partitioning, and compute scaling strategies. Define RBAC policies, ensure compliance with data governance standards, and mentor engineers by setting standards for CI/CD, testing, and cloud-native delivery. Partner with AI/ML, analytics, and business teams to enable real-time and batch data activation use cases.
Required Qualifications
- 8+ years of experience in data engineering
- experience delivering complex, enterprise-scale data solutions
- Azure experience
- Advanced technical expertise in Cloud based data warehouses
- Spark
- Delta Lake
- Azure Services
- data integration
- data modeling
- performance optimization
- Proven experience in building and optimizing large-scale ETL/ELT pipelines
- data lakehouse architectures
- Solid understanding of data lakehouse modeling
- data warehousing
- performance tuning
- Experience with Infrastructure as Code (Terraform, ARM templates)
- DevOps tools (Git, Azure DevOps, Jenkins)
- Familiarity with RBAC
- data security
- compliance frameworks
- Strong communication and collaboration skills
- ability to influence technical direction
- clarify tradeoffs
- align engineering decisions across teams and stakeholders
- Experience with Agile methodologies
- working in cross-functional product teams
- Demonstrated ability to lead through influence
- mentor engineers
- manage technical ambiguity
- drive outcomes across a broad scope of products, platforms, and stakeholders
Desired Qualifications
- Azure experience preferred
- experience with Customer 360 data products
- identity resolution
- customer profile enrichment
- activation use cases
- Experience designing and supporting streaming data solutions
- Kafka or similar event streaming platforms
- Martech exposure
- experience supporting marketing
- personalization
- campaign
- loyalty
- customer engagement data use cases
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