Adobe - EDA Architect - Python/Scala

About the Role :

At Adobe, our Enterprise Data & Analytics (EDA) team builds intelligent, scalable, and resilient data products using cutting-edge cloud and AI technologies. Were looking for a passionate Architect to help lead the evolution of our data platform strategydesigning innovative solutions that automate, augment, and accelerate the development lifecycle of data products and services.

This is your opportunity to shape Adobes next generation of AI-driven data platforms that power strategic decision-making across the company.

What You'll Do :

- Lead architecture and design of cloud-native data platforms (AWS/Azure), aligned with business and technology objectives.

- Drive integration of AI/ML into data and analytics development workflows to improve speed, efficiency, and quality.

- Conceptualize and communicate architectural visions to stakeholders across engineering, product, and business teams.

- Define scalable, modular, and secure design standards, frameworks, and reusable components.

- Create a Point of View (POV) on emerging trends or capabilities that influence EDAs target state architecture, business context, and strategic roadmap.

- Build PoCs or prototypes for point solutions that address business opportunities with tangible impact and measurable benefits.

- Collaborate with cross-functional teams to turn complex business challenges into effective data solutions.

- Guide and mentor engineering teams on solution design and implementation of prioritized architectural initiatives.

- Mentor engineers, conduct design/code reviews, and promote a culture of continuous improvement and engineering excellence.

What You'll Need :

- 16+ years of experience in software engineering, including 3 to 5 years as a Data/AI ML Cloud Architect.

- Deep hands-on experience building cloud-based data lakes and applications using tools such as: AWS/Azure: S3/ADLS, serverless functions, EMR, ECS/EKS, Databricks, Spark,

- Proficiency in SQL and programming languages like Python, Scala, or Java.

- Experience working with feature stores, vector databases, and embedding-based search or retrieval systems.

- Understanding of generative AI, large language models (LLMs), and their potential applications in data products.

- Proven experience integrating AI/ML models into data pipelines, from development to deployment and monitoring.

- Familiarity with machine learning lifecycle tools such as MLflow, SageMaker, Azure ML, or Vertex AI.

- Expertise in Kubernetes, Docker, and container deployment strategies.

- Strong understanding of distributed computing, streaming architectures, and big data

performance optimization.

- Proven leadership in Agile/Scrum environments and managing globally distributed teams.

- Excellent communication, stakeholder management, and mentoring skills.

- Bachelors degree in computer science, Information Systems, or a related field.