Senior Data Platform Engineer

Reply · Seattle, Washington

  • Senior
  • Full-time
  • Posted 2026-09-02
  • Confirmed live on 25 September 2026

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Job description

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<div>Valorem Reply, part of the Reply Network, is a leader in Microsoft-based IT solutions. We support and advise our Giant Tech customers in all aspects of Microsoft, and other industry-leading technologies. From designing and developing custom solutions and low-code solutions, to implementing and managing them seamlessly, Valorem Reply helps customers unlock the potential of their IT infrastructure to enable their sales and partner initiatives.&nbsp;</div>
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<p><span data-contrast="auto">Accelerate your career by working with&nbsp;the largest&nbsp;technology clients&nbsp;in the world. Join this&nbsp;diverse team that thrives on innovation&nbsp;and making a&nbsp;real-world&nbsp;impact.&nbsp;</span><span data-ccp-props="{}">&nbsp;</span></p>
<p>This role sits at the intersection of platform engineering, data engineering, and data product development within financial services applications. Leading with platform engineering - and with data engineering as the assumed foundation - the engineer builds reusable platform capabilities and data products that let quantitative researchers discover, access, and consume data across a complex, disparate landscape, and then accelerates the good prototypes to production.<br>• &nbsp; &nbsp;Design, build, and enhance platform capabilities within Databricks and related technologies.<br>• &nbsp; &nbsp;Evaluate and adopt emerging platform features and technologies; run the self-assessments and technology evaluations research initiatives depend on.<br>• &nbsp; &nbsp;Improve governance, automation, observability, security, and operational excellence.<br>• &nbsp; &nbsp;Help define the target-state architecture for custom platform.</p>
<p>• &nbsp; &nbsp;Work through AI agents by default. Use agentic tools to design, build, test, and operate, and know when to trust them versus verify.</p>
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Required Skills
• Hands-on Databricks experience across workspace, notebooks, and jobs, plus building platform capabilities on it (not just using it).
• Strong Python and SQL.
• Platform-engineering foundation: infrastructure as code with Terraform and modern CI/CD.
• Data governance and observability in a managed environment (e.g. Unity Catalog, lineage, monitoring).
• Strong workflow orchestration experience with Apache Airflow (we use Astro / Astronomer).
• Building and operating data pipelines that integrate disparate, heterogeneous data sources.
• Building reusable, self-service data products for non-engineer end users (researchers/analysts).
• An AI-first mindset: fluent with agentic coding tools (e.g. Claude Code) and eager to make them central to how the team works.

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