Senior Data Solutions Engineer Job Listing at AMD in Warsaw, Masovian Voivodeship (Job ID 84617-en-us)

Description

WHAT YOU DO AT AMD CHANGES EVERYTHING 

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you'll discover the real differentiator is our culture. We push the limits of innovation to solve the world's most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.  Together, we advance your career.  

THE ROLE: 

As the Senior Data Engineer you will define, design, and align our next‑generation data platforms. You will take end‑to‑end ownership of data architecture and core data engineering capabilities, translating complex business and engineering requirements into scalable, reliable, and high‑performance data solutions. As a senior technical contributor, you will work hands‑on across the full data stack starting from driving data modeling, pipeline design, platform reliability, and performance at scale up to setting engineering standards and best practices. You will collaborate closely with software engineers, data scientists, and product teams to ensure alignment and enable data‑driven innovation.

This is a highly influential role within the engineering organization, where you will mentor other engineers, provide architectural leadership, and help shape AMD's long‑term data platform strategy to support the delivery of high‑quality, industry‑leading technologies.  

YOU ARE: 

A Senior Data Engineer who thrives as a hands‑on individual contributor, designing, building, and evolving complex data platforms at enterprise scale. You bring strong data architecture fundamentals together with deep practical experience implementing data pipelines, storage layers, and processing systems that are reliable, performant, and maintainable. You work closely with other engineers to turn abstract requirements and high‑level designs into working systems, making thoughtful trade‑offs to balance scalability, performance, and delivery. You are motivated by technically challenging problems—especially those involving scale, complexity, or ambiguity—and you take ownership of solving them end‑to‑end through code, design, and continuous improvement.

KEY RESPONSIBILITIES: 

• Design, build, and evolve end‑to‑end data platforms, including data lakes/lakehouses, analytics systems, ingestion pipelines, and supporting infrastructure, with a strong focus on scalability, reliability, and performance.
• Translate business, analytics, and product requirements into concrete technical solutions, including logical and physical data models, pipeline designs, platform configurations, and well‑documented architectural decisions.
• Implement and optimize core data engineering components across ingestion, storage, processing, and analytics layers, ensuring high data quality, fault tolerance, security, and operational stability.
• Evaluate and apply modern data technologies and architectural patterns (cloud services, storage engines, compute frameworks, data formats, governance mechanisms) based on hands‑on experimentation, performance analysis, and cost considerations.
• Take ownership of complex data platform problems, debugging and resolving issues related to scale, performance, data correctness, and system reliability across the data stack.
• Collaborate closely with other engineers and adjacent teams to integrate data platforms with products and services, contributing code, reviews, and technical input to ensure consistent, high‑quality implementations.

EXPERIENCE: 

• 8+ years of hands‑on experience in data engineering and building large‑scale data platforms (batch and/or streaming), with demonstrated ownership of production systems end‑to‑end (design → implementation → operations).

• Proven experience designing and implementing data architectures that support AI/ML workloads, including reliable feature generation pipelines, training/serving data layers, and patterns for batch + real‑time processing.
• Strong practical experience with lakehouse / data lake architectures and modern data platform components (object storage, distributed compute, metadata/catalog, orchestration), including performance tuning and cost optimization.
• Solid understanding of MLOps / ML lifecycle needs from a data perspective (dataset/version management, lineage, reproducibility, governance controls, monitoring for data drift/quality)—and the ability to build the data plumbing that makes these workflows dependable.
• Proficiency in Python and SQL, with the ability to write production‑quality code, reason about distributed performance, and debug issues across compute/storage/network boundaries.
• Experience working with structured and unstructured data (e.g., text, images, logs), including data preparation patterns for analytics, ML training, and generative AI use cases.
• Working knowledge of cloud infrastructure and distributed systems, including storage/compute primitives, networking considerations, and strategies for reliability and cost efficiency at scale.
• Demonstrated ability to collaborate closely with data scientists, ML engineers, and platform teams to translate ML/analytics needs into production‑ready data interfaces (datasets, contracts, SLAs) and scalable implementations.
• Excellent written and verbal communication skills in English, with proven experience presenting complex AI/data architecture concepts to both technical and executive audiences.

ACADEMIC CREDENTIALS: 

PhD or MSc degree in Computer Engineering, Software Engineering, Computer Science

#On-site / hybrid role in Poland, Gdansk

#LI-CC5  

#LI-hybrid

Benefits offered are described:  AMD benefits at a glance.

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law.   We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position.  AMD's “Responsible AI Policy” is available here.

This posting is for an existing vacancy.