Role Overview
We are seeking a Senior Data Product Engineer to join our team in [city], [stateProvince], [country]. The successful candidate will lead the design and implementation of enterprise Data Product standards, architecture patterns, and engineering practices within the Databricks ecosystem.
What You Will Do
The successful candidate will partner with business stakeholders, Risk domain teams, Data Product Owners, and technology leadership to identify high-value data products that support critical business use cases and analytics outcomes. They will also architect and build multiple end-to-end MVP Data Products in Databricks, develop scalable data pipelines, and collaborate with Data Engineers, Data Architects, Governance teams, and platform teams.
Why It Might Be a Fit
The successful candidate will provide technical leadership and mentorship to engineering teams while driving alignment between strategic business objectives and practical delivery execution. They will also support proposal development, solution architecture discussions, effort estimation, and client presentations related to enterprise Data Product and Databricks transformation initiatives.
Requirements
- Minimum 10+ years of experience in Data Engineering, Data Architecture, Analytics Engineering, or Enterprise Data Management.
- Minimum 5+ years of experience designing and implementing modern cloud-based data platforms and data products.
- Minimum 4+ years of hands-on Databricks experience, including Delta Lake, Unity Catalog, Workflows, MLflow, and Lakehouse architecture patterns.
- Minimum 5+ years of experience designing scalable data architectures and distributed data processing solutions.
- Minimum 4+ years of experience building enterprise data pipelines using Spark, Python, SQL, and cloud-native technologies.
- Minimum 3+ years of experience implementing Data Product operating models, Data Mesh concepts, domain-driven data ownership, or product-oriented data delivery approaches.
- Minimum 3+ years of experience delivering cloud-based solutions on Azure, AWS, or Google Cloud Platform.
- Experience implementing data governance, metadata management, data quality frameworks, lineage, and security controls within modern data platforms.
- Experience designing reusable engineering standards, architecture patterns, and platform accelerators that support large-scale enterprise adoption.
- Experience engaging directly with business stakeholders to translate business requirements into scalable data product solutions.
- Strong communication and consulting skills with the ability to lead architecture workshops, executive discussions, and technical solution reviews.
Benefits
- Medical, dental, and vision insurance with an employer contribution
- Flexible spending or health savings account
- Life and AD&D insurance
- Short and long term disability coverage
- Paid time off
- Employee assistance
- Participation in a 401k program with company match
To apply for this job please visit career8.successfactors.com.

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