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Engineering Director

CompraTica Empleos

EMP:Management
Remote
Tiempo Completo
Remoto
0 vistas

Descripción

<p>Here at Precision AQ we are building a Data Hub, a centralized platform team, to be responsible for consolidating legacy data infrastructure, establishing enterprise data foundation and governance and enabling AI/ML capabilities across the organization.

  The Data Hub is moving from strategy to execution.

We have a charter, a roadmap, executive sponsorship, and a clear mandate: consolidate fragmented data pipelines into a governed, scale able platform that serves multiple business units and product lines.

We are now hiring an engineering leader who can build and run the team.

</p> <p><strong>Job Summary:</strong></p> <ul> <li>Stand up and scale a high-performing engineering team</li> <li>Own day-to-day engineering operations: sprint delivery, technical quality, capacity planning</li> <li>Drive technical excellence: architecture decisions, code quality, DevOps/GitOps practices, production reliability</li> <li>Be the primary escalation point for technical blockers, cross-team dependencies and delivery risks</li> <li>Partner with the SVP on hiring, team development, vendor relationships and strategic planning</li> </ul> <p><strong>Key.

Responsabilidades

:

  • Engineering Team Leadership: Build, lead, and develop a team of data engineers, analytics engineers, and platform engineers

    Set expectations, run 1:1s, manage performance, and create an environment where strong engineers want to stay and grow.

    You are accountable for the team’s output, quality, and morale.

     </li> <li>Sprint Delivery and Capacity Management: Own the engineering delivery cadence.

    Run sprint planning, standups, and retrospectives.

    • Manage capacity across concurrent workstreams (platform build, migrations, feature development).
    • Ensure commitments are realistic and met.

    </li> <li>Technical Design and Architecture: Lead technical design reviews and architectural decisions.

    • Ensure solutions are scalable, maintainable, and aligned with our medallion data architecture.

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