AMD

3 months ago

Data Engineer Architect.

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Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Define, design, and drive next-generation data platform architecture, including data lakes/lakehouses, analytics platforms, integration patterns, and supporting infrastructure. Translate business, analytics, and product requirements into logical/physical data models and platform specs. Evaluate and recommend modern data technologies to optimize scalability, performance, reliability, and cost. Serve as the escalation point across ingestion, storage, processing, analytics, and governance, and lead cross-functional architectural alignment.

Location: Gdansk

Workplace: Hybrid

Employment Type: Full time

Job Function: Administration & Executive Assistance

Seniority: Sr. Manager level

Key Responsibilities

•Define, document, and govern end-to-end data architectures, including data lakes/lakehouses, analytics platforms, integration patterns, and supporting infrastructure.
•Translate business, analytics, and product requirements into actionable data architecture designs, including logical/physical data models, platform specifications, and interface contracts.
•Evaluate, select, and recommend modern data technologies and architectural patterns to optimize scalability, performance, reliability, and cost efficiency.
•Drive the design and evolution of core data platform components with a focus on robustness, data quality, security, fault tolerance, and operational excellence.
•Act as the architectural escalation point for complex data platform issues and lead cross-functional architectural collaboration with teams across engineering, platform, security, analytics, and product.

Key Requirements

•12+ years of experience in data architecture or data engineering, including at least 5 years in a senior/lead/principal role driving architecture.
•Expertise designing data architectures that support AI/ML workloads, including feature stores, pipelines, and batch/streaming processing.
•Hands-on experience with modern AI/ML and data platforms, including cloud-native lake house architectures and ML tooling for experimentation, training, deployment, and monitoring.
•Deep understanding of MLOps and the ML lifecycle, including data versioning, experiment tracking, model governance, CI/CD for ML, and production monitoring.
•Proficiency in programming and data languages used in AI/ML ecosystems (e.g., Python, SQL) and the ability to reason about scalability and reliability of data pipelines.

Experience:12+ yearsData architectureData engineeringAI/MLMLOps

Education:Master's

Skills:CommunicationCollaboration

Languages:English

Tech Stack:PythonSQLAI/MLMLOpsCI/CDData lakesLake housesFeature storesStreamingBatch processingData governanceData securityIntegration patterns

Company Brief

AMD

Designs and produces semiconductor products including CPUs, GPUs, and adaptive SoCs for consumer, enterprise, and embedded markets, competing across PCs, data centers, and gaming industries.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1969

Glassdoor: 3.9

Website LinkedIn

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AMD