Data Platform Engineering Manager

Global Sports Jobs Limited

Phoenix (AZ)

On-site

USD 180,000 - 240,000

Full time

14 days+

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Job summary

Warner Bros. Discovery is seeking an Engineering Manager to lead a small team of 2-5 engineers delivering Data & Audience Platform capabilities across data processing, self-service enablement, metadata, reliability and governance.

This frontline leadership role focuses on clarity, roadmap execution, and production-system reliability with cost awareness. As part of the DICE team, you will drive platform modernization, establish SLIs/SLOs, and collaborate with product, analytics and engineering

Qualifications

Bachelor's degree or higher in CS, Engineering or related field.
12+ years of professional software or data engineering experience.
3+ years of direct management of engineers.
Hands-on experience building and operating large-scale data platforms, distributed systems or cloud infrastructure.
Strong understanding of batch and stream processing, data lakehouse architecture, metadata, governance, access control, orchestration, observability and cost management.
Knowledge of distributed systems, cloud platforms, engineering operations and enterprise-grade governance.
Proven ability to lead delivery of technical programmes across multiple stakeholders.
Strong operational excellence mindset, including incident management, monitoring, SLOs, runbooks, RCA/COE practices and production readiness.
Experience driving automation, developer productivity and scalable engineering workflows.
Sufficient hands-on depth to review designs and code and make sound technical trade-offs.
Strong written and verbal communication skills.

Responsibilities

Lead a small team of 2-5 engineers delivering foundational Data & Audience Platform capabilities used across analytics, data engineering, business intelligence, operational workflows and AI/ML enablement.
Own execution across data collection, batch and streaming data processing, metadata, observability, cost efficiency and self-service platform capabilities within the team's domain.
Build a strong engineering team culture focused on ownership, customer impact, reliability, inclusion and high standards, coaching engineers to improve technical judgment, execution quality, stakeholder communication and operational discipline.
Hire, develop and retain engineers, grow tech leads and emerging technical leaders, and regularly engage stakeholders to communicate status, risks and key decisions.
Own the team's backlog and delivery roadmap, translating departmental goals into prioritised, well-scoped work matched to available engineering capacity.
Modernise platform capabilities across storage, compute, orchestration, ingestion, access, metadata and self-service workflows, and partner with peer managers to align priorities and reduce duplication of effort.
Establish and maintain strong operational practices across owned systems, including SLIs/SLOs, dashboards, alerts, runbooks, incident response, RCAs/COEs and post-incident learning, while improving alert quality, reducing manual toil and increasing automation.
Drive a culture of proactive reliability engineering, cost-aware design and continuous improvement across platform operations.
Drive adoption of metadata, lineage, ownership, classification, data quality, access review and lifecycle management practices, and improve the discoverability and trustworthiness of data assets through cataloguing, documentation, schema management and data product standards.
Deliver self-service onboarding, automated access workflows, reusable templates and standard platform patterns that reduce manual engineering dependency and improve developer experience for teams building, deploying, operating and governing data products.
Partner with engineering, product, program management, analytics, data science, operations engineering, security, governance, privacy and business stakeholders, embedding controls into platform workflows rather than treating them as manual afterthoughts.