Senior Software Development Engineer, Data Science & Cloud Engineering

Adobe•San Jose, CA

About The Position

Changing the world through digital experiences is what Adobe's all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We're passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We're on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! Join Adobe's mission to transform the future of creativity and data-driven experiences. We are seeking a senior computer scientist who brings a unique blend of software engineering, data science, and DevOps expertise to build scalable, intelligent systems that power Adobe's next-generation platforms. This role fits a person who excels software development fundamentals, large-scale data technologies, and cloud infrastructure. They also reflect Adobe's core values of creativity, ownership, excellence, and authenticity. Adobe strongly fosters and values its leaders. We look for individuals who lead with integrity and are role models for accomplishing business initiatives with the highest degree of trust, who create an inclusive culture where people do their best work, and who improve the contributions of the team.

Requirements

Education: Bachelor's or higher in Computer Science, Engineering, or related field.
Experience: 5+ years in software development with strong coding skills in Java, C++, or mobile platforms.
Hands-on experience with PySpark and distributed data processing frameworks.
Familiarity with cloud platforms (AWS, Azure) and data services.
Skills: Solid understanding of computer science fundamentals: algorithms, complexity, parallelism, and system design.
Knowledge of DevOps practices for data environments.
Strong problem-solving and debugging skills.
Strong written and verbal communication and interpersonal skills.

Nice To Haves

Experience with MLOps, CI/CD pipelines, and containerization (Docker/Kubernetes).
Exposure to cost optimization and performance tuning for Spark workloads.

Responsibilities

Software Engineering : Design and develop robust, scalable applications and services across client-side (C++, iOS/Swift, Android/Java) or server-side (Java) environments.
Own projects through the full software development lifecycle: requirements gathering, architecture, coding, testing, deployment, and maintenance.
Apply strong computer science principles: algorithms, data structures, design patterns, and system architecture.
Tune code to address high performance and load requirements.
Respond to urgent production issues requiring fast resolution and deployment of code fixes/updates
Data Science Engineering : Build and optimize PySpark jobs for large-scale data processing.
Work with modern data ecosystems: Apache Hadoop, AWS EMR, Azure Databricks, or Azure Data Explorer (ADX).
Implement machine learning workflows and integrate predictive analytics into production systems.
Collaborate with the team to visualize, design, and experiment with data-driven agentic workflows.
DevOps & Cloud Operations : Manage configurations and deployments for (elastic compute) Spark environments.
Participate in system upgrades (OS, libraries, Spark versions) and ensure compatibility with data pipelines.
Analyze cost dashboards and optimize resource utilization for Spark jobs.
Provide cost projections for new Spark jobs in development.
Collaboration & Leadership : Partner with teams (engineering, product, UX) to deliver impactful solutions.
Communicate proactively: share successes, raise challenges early, and ask for help when needed.
Contribute to a culture of innovation, inclusivity, and continuous improvement.