Drive modernization of legacy data systems by defining strategies to transition from traditional architectures to modern, cloud-native, and AI-driven platforms while maintaining business continuity.
Accelerate real-time data delivery to meet urgent business needs by implementing streaming and low-latency data solutions that enable faster decision-making.
Champion agility and speed in platform development by fostering a culture of rapid iteration, automation, and continuous improvement across the SDLC.
Adopt a platform-as-a-product mindset, ensuring scalability, usability, and cost efficiency while balancing innovation with financial responsibility.
Lead engineering initiatives that integrate multi-cloud and AI infrastructure, optimizing for performance, cost, and security.
Collaborate cross-functionally to align platform capabilities with evolving business priorities, competitive pressures, and cultural transformation goals.
Promote cutting-edge technology adoption and open new horizons for the organization by leveraging modern tools and frameworks (e.g., Snowflake, Kafka, Kubernetes, AI/ML stacks).
Instill engineering excellence through robust design standards, code quality, and reliability practices, ensuring the platform can scale with business demands.
Drive cultural and technological change by inspiring teams to embrace innovation, experimentation, and a forward-thinking approach to data and AI.

Requirements

15+ years of experience in Data, backend, streaming, API management, data engineering, or platform engineering, with ideally 4+ years in ML/AI.
5+ years of engineering management experience, ideally in data platform role.
Deep technical understanding of modern data architecture (lakehouse, streaming, data mesh, serverless pipelines, iceberg, open table formats)
Background in broadband or telecommunications would be highly preferred.
Strong leadership in matrixed organizations, skilled in driving alignment across engineering, AI, and business units
Expertise in Data and ML Ops and data infrastructure development.
Strong understanding of cloud-native infrastructure and scalable ML systems.
Proven ability to align data and AI platform strategy with business and product objectives.
Passion for mentorship, coaching, and team development.
Excellent communication skills, with the ability to collaborate across technical and non-technical teams.
Strong ability to evaluate build vs. buy decisions for ML tooling and infrastructure.
Experience with cost optimization and platform observability frameworks.

Benefits

Best-in-class Benefits to eligible employees
Array of options, expert guidance and always-on tools

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

data engineeringstreamingAPI managementmachine learningdata architecturedata meshserverless pipelinesdata infrastructure developmentML Opscost optimization

Soft skills

leadershipcollaborationmentorshipcoachingcommunicationalignmentinnovationexperimentationteam developmentdriving change