Software Engineer II, BigQuery UI, Adoption Pod

📍 Job Overview

Job Title: Software Engineer II, BigQuery UI, Adoption Pod

Company: Google

Location: Kraków, Lesser Poland Voivodeship, Poland; Warsaw, Masovian Voivodeship, Poland

Job Type: Full-time

Category: Software Engineering / Cloud Data Analytics

Date Posted: July 16, 2026

Experience Level: 0-2 Years

Remote Status: On-site

🚀 Role Summary

• Contribute to the development and enhancement of the BigQuery user interface within the Google Cloud Console, focusing on the Adoption Pod.

• Write, test, and deploy high-quality, efficient code for front-end components and features, adhering to Google's best practices.

• Collaborate closely with backend engineers, Product Managers, UX Researchers, and UX Designers to deliver an exceptional user experience for data analytics products.

• Debug, triage, and resolve product or system issues by analyzing root causes and their impact on service operations and quality.

• Participate in code reviews, providing constructive feedback to peers to ensure code quality, accuracy, and adherence to style guidelines.

📝 Enhancement Note: While the title is "Software Engineer II," the minimum qualifications suggest an entry-level to early-career role (1 year of experience). The "Adoption Pod" focus implies a strategic emphasis on user onboarding and initial engagement with BigQuery. This role is deeply embedded within the Google Cloud Platform (GCP) ecosystem, specifically targeting data analytics users.

📈 Primary Responsibilities

• Design, build, and improve front-end components and features for Cloud Data Analytics products, with a specific focus on the BigQuery user interface (go/bqui) within the Google Cloud Console (go/pantheon).

• Collaborate with BigQuery backend teams to ensure seamless integration and optimal performance of UI features.

• Work cross-functionally with Product Managers, UX Researchers, and UX Designers to translate user needs and product requirements into intuitive and powerful UI solutions.

• Contribute to the documentation and educational content for BigQuery, adapting materials based on product updates and user feedback to improve adoption.

• Debug and resolve technical issues by analyzing the sources of problems, assessing their impact on hardware, network, or service operations, and implementing effective solutions.

• Write product or system development code, ensuring it is testable, efficient, and adheres to Google's coding standards and style guidelines.

• Participate in code reviews, offering constructive feedback to fellow developers to maintain high code quality and best practices.

• Collaborate with other Data Analytics UI teams and Google Cloud Platform (GCP) teams to create and utilize shared components within the Cloud Console.

📝 Enhancement Note: The responsibilities highlight a full-stack engineering involvement within a specific product pod (Adoption Pod). The emphasis on collaboration with backend, PM, and UX teams, alongside code quality and debugging, is typical for a mid-level software engineering role within a large tech organization. The explicit mention of "go/bqui" and "go/pantheon" indicates a need for familiarity with internal Google documentation and project naming conventions.

🎓 Skills & Qualifications

Education:

• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.

• Master’s degree in Computer Science or a related technical field is preferred. Experience:

• Minimum of 1 year of experience in software development.

• Minimum of 1 year of experience working with data structures and algorithms.

• Experience in developing with at least one programming language such as Python, C, C++, Java, or JavaScript.

• Preferred: 1 year of experience with TypeScript, JavaScript, Angular, Java, or GraphQL. Required Skills:

• Proficiency in software development principles and practices.

• Strong understanding of data structures and algorithms.

• Experience with at least one major programming language (e.g., Python, C, C++, Java, JavaScript).

• Ability to triage, debug, and resolve technical issues.

• Experience in writing and reviewing code, ensuring adherence to best practices.

• Familiarity with front-end development concepts.

• Excellent problem-solving and analytical skills.

• Strong communication and collaboration skills, with experience working in cross-functional teams. Preferred Skills:

• Experience with TypeScript, JavaScript, and front-end frameworks like Angular.

• Knowledge of GraphQL for API development.

• Experience with UI design principles and user experience considerations.

• Familiarity with cloud computing platforms, particularly Google Cloud Platform (GCP).

• Experience with data analytics tools and concepts, specifically BigQuery.

• Understanding of large-scale system design and distributed computing.

📝 Enhancement Note: The qualifications clearly segment into minimum and preferred. The minimum requirements are typical for an entry-level Software Engineer (SWE II at Google often implies 1-3 years of experience). The preferred qualifications strongly point towards a front-end or full-stack role within a web application context, with a clear emphasis on modern JavaScript/TypeScript ecosystems and data-intensive applications.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrations of code quality, including well-structured, maintainable, and efficient code samples.

• Examples of problem-solving through code, showcasing debugging and issue resolution capabilities.

• Contributions to documentation or educational content, illustrating clarity and user-centric communication.

• Evidence of collaborative development, such as contributions to shared codebases or participation in team projects.

• Projects demonstrating proficiency in data structures and algorithms, showcasing practical application. Process Documentation:

• Candidates may be asked to discuss their approach to code reviews, including how they provide constructive feedback and ensure adherence to best practices.

• Examples of how they have triaged and debugged complex technical issues, detailing their analytical process and resolution strategies.

• Discussion of their experience in contributing to or improving technical documentation and educational materials.

• Insights into their workflow for designing, building, and improving software components.

📝 Enhancement Note: For a Software Engineer role, a traditional "operations" portfolio isn't expected. Instead, the portfolio should showcase software development artifacts. This includes code repositories (e.g., GitHub), personal projects, contributions to open-source, or academic projects that demonstrate the required technical skills and problem-solving abilities. The emphasis is on the process of development and the quality of the output.

💵 Compensation & Benefits

Salary Range:

• Poland: zł206,000 - zł212,000 PLN per year.

• This range is for the base salary and does not include potential bonuses or equity. Benefits:

• Bonus Target: Approximately 15% of base salary, performance-dependent.

• Equity: Potential for stock grants, reflecting long-term company performance.

• Comprehensive Benefits Package: Includes health insurance, retirement plans, paid time off, parental leave, and wellness programs, consistent with Google's global offerings.

• Professional Development: Opportunities for training, conferences, and continuous learning.

• Work-Life Balance: Support for maintaining a healthy balance through various programs and policies.

Working Hours:

• Standard full-time working hours are typically around 40 hours per week.

• Flexibility may be offered based on team needs and project deadlines, but the role is designated as on-site.

📝 Enhancement Note: The provided salary range is specific to Poland. The "15% bonus target" and "equity" are standard components of compensation at Google for this level. The general mention of "benefits" is expanded to include typical offerings for large tech companies, especially Google, which are known for generous employee packages. The "working hours" are inferred from the standard full-time employment type and the on-site requirement.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology (Software & Cloud Computing)

Company Size: Large (100,000+ employees globally)

Founded: 1998. Google has a long history of innovation, focusing on organizing the world's information and making it universally accessible and useful, which has expanded into cloud computing, AI, and a vast array of digital services.

Team Structure:

• The BigQuery UI team is part of Google Cloud's Data Analytics division.

• It operates as a "pod" (Adoption Pod), suggesting a cross-functional, agile team focused on a specific user journey or product area.

• The team likely includes Software Engineers, Product Managers, UX Designers, and UX Researchers, working closely together.

• Reporting structure is hierarchical within Google, but pod-based work encourages collaborative decision-making. Methodology:

• Agile Development: Teams typically work in sprints, focusing on iterative development and continuous delivery.

• Data-Driven Decisions: Emphasis on using data analytics and user feedback to inform product development and prioritize features.

• User-Centric Design: Strong focus on understanding user needs and designing intuitive, efficient interfaces.

• Engineering Excellence: Commitment to high code quality, scalability, reliability, and performance.

Company Website: https://www.google.com

📝 Enhancement Note: Google's culture is renowned for innovation, data-driven decision-making, and a focus on impact. The "Adoption Pod" structure within BigQuery UI indicates a specialized team within a larger product group, emphasizing agility and focused problem-solving for user onboarding and initial engagement.

📈 Career & Growth Analysis

Operations Career Level: Software Engineer II (Early to Mid-Career)

This level typically signifies an engineer with 1-3 years of professional experience who can work independently on well-defined tasks and contribute to larger features. They are expected to have a solid grasp of fundamental computer science concepts and programming languages, and begin to develop expertise in specific areas like UI development for cloud data products.

Reporting Structure:

The role reports to an Engineering Manager within the BigQuery UI team. Collaboration will be extensive with Product Managers, UX Designers, UX Researchers, and fellow Software Engineers across Cloud Data Analytics and GCP teams.

Operations Impact:

This role directly impacts Google Cloud's success by improving the user experience of BigQuery. A well-designed and intuitive UI for BigQuery is critical for:

• Customer Adoption & Retention: Making it easier for new users to get started and existing users to leverage advanced features.

• Product Competitiveness: Differentiating BigQuery from competitors by offering a superior user experience.

• Data Democratization: Enabling a wider range of users (analysts, scientists, administrators) to access and derive insights from their data.

• Revenue Growth: Driving adoption and usage of Google Cloud's data analytics services.

Growth Opportunities:

• Technical Specialization: Deepen expertise in front-end technologies (TypeScript, Angular), cloud platforms (GCP), and data analytics tools (BigQuery).

• Cross-functional Collaboration: Develop strong skills in working with Product Management and UX teams to influence product direction.

• System Design: Gain experience in designing and building scalable, robust UI components for large-scale cloud services.

• Mentorship: Opportunity to mentor junior engineers as experience grows.

• Career Progression: Potential to advance to Senior Software Engineer, Staff Engineer, or leadership roles within Google Cloud.

📝 Enhancement Note: The "Operations" context here is interpreted through the lens of how a Software Engineer role contributes to the operational success and growth of a product line (BigQuery) within the broader company operations. The impact is measured in terms of user adoption, product competitiveness, and revenue.

🌐 Work Environment

Office Type: Google operates modern, collaborative office spaces designed to foster innovation and teamwork. These environments typically include open-plan work areas, private offices, meeting rooms, collaboration zones, and amenities like cafes and recreational facilities.

Office Location(s): Kraków and Warsaw, Poland. These are major tech hubs offering access to talent and infrastructure.

Workspace Context:

• Collaborative Environment: Expect a dynamic workspace where teamwork is paramount. Regular team sync-ups, brainstorming sessions, and cross-functional meetings are common.

• Tooling and Technology: Access to Google's cutting-edge internal tools, development environments, and robust cloud infrastructure. High-performance workstations and reliable network connectivity are standard.

• Team Interaction: Frequent interaction with immediate team members (engineers, PMs, UX), as well as engineers from other GCP teams and backend BigQuery services. The on-site nature facilitates spontaneous discussions and problem-solving.

Work Schedule:

The role is on-site, implying a standard work week spent at the designated Google office. While Google often supports flexible working arrangements, the primary expectation for this role is in-office presence to maximize collaboration and integration with the team and its processes. A typical full-time schedule would apply, with potential for project-driven adjustments.

📝 Enhancement Note: The description emphasizes the collaborative and technologically advanced nature of Google's office environments, which are designed to support the company's innovative culture and agile development methodologies. The on-site requirement is framed as a facilitator of this collaborative ecosystem.

📄 Application & Portfolio Review Process

Interview Process:

The typical Google interview process for Software Engineers is rigorous and multi-stage:

1. Online Assessment/Recruiter Screen: Initial screening of resume and potentially an online coding challenge.

2. Technical Phone Screens (1-2): Focused on coding, data structures, algorithms, and problem-solving abilities. You'll likely solve problems on a shared document.

3. On-site Interviews (Virtual or In-Person): Typically 4-5 interviews covering:

• Coding Interviews (2-3): Solving algorithmic problems, often with a focus on efficiency and correctness.
• System Design Interview (1): Designing scalable systems, often focusing on distributed systems or large-scale applications.
• Behavioral/Googliness Interview (1): Assessing cultural fit, teamwork, leadership potential, and how you handle challenging situations.

1. Hiring Committee Review: Your interview feedback is compiled and reviewed by a committee to ensure fair and consistent evaluation.

2. Team Matching (if applicable): For some roles, you might interview with a general SWE team first and then be matched with a specific pod/project. For this role, it's likely a direct hire into the BigQuery UI team.

Portfolio Review Tips:

• GitHub Profile: Ensure your GitHub profile is up-to-date and showcases relevant projects. Highlight code quality, clear READMEs, and well-documented code.

• Project Selection: Choose projects that demonstrate your proficiency in languages like Python, Java, JavaScript/TypeScript, and your understanding of data structures and algorithms. Front-end projects using Angular or similar frameworks are highly relevant.

• Problem-Solving Examples: Be prepared to discuss specific technical challenges you've faced and how you solved them, ideally with code examples.

• Collaboration Evidence: If you have open-source contributions or significant team projects, highlight your role and contributions.

• Documentation: Showcase any technical writing or documentation efforts.

Challenge Preparation:

• Coding: Practice coding problems on platforms like LeetCode, HackerRank, or Coderbyte. Focus on medium to hard difficulty problems related to arrays, strings, trees, graphs, dynamic programming, and recursion.

• System Design: Study common system design patterns. Understand concepts like scalability, availability, consistency, load balancing, caching, and database choices. Prepare to design systems like a URL shortener, a social media feed, or a distributed cache.

• Behavioral: Prepare STAR method (Situation, Task, Action, Result) answers for common behavioral questions about teamwork, leadership, conflict resolution, and handling failure.

• BigQuery & GCP: Familiarize yourself with BigQuery's capabilities and the general architecture of Google Cloud Platform. Understand the BigQuery UI's purpose and common user workflows.

📝 Enhancement Note: The interview process is detailed to provide actionable preparation steps. The portfolio advice is tailored to a software engineering role, emphasizing code quality, problem-solving, and collaboration artifacts, rather than traditional operations process documentation.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Python (strong preference), C, C++, Java, JavaScript.

• Front-end Development: TypeScript (preferred), JavaScript, Angular (preferred).

• UI Frameworks/Libraries: Familiarity with modern front-end frameworks is crucial.

• Version Control: Git (mandatory).

• Development Environment: Google's internal development tools and infrastructure.

Analytics & Reporting:

• BigQuery: Directly working with and enhancing the BigQuery UI. Understanding BigQuery's data warehousing capabilities is essential.

• Data Analytics Tools: Familiarity with how users interact with data analytics products.

• Internal Google Tools: Various internal tools for logging, monitoring, and debugging.

CRM & Automation:

• While not a CRM or automation role in the traditional sense, understanding how UI features drive user adoption and engagement within the broader Google Cloud ecosystem is key.

• Cloud Platforms: Google Cloud Platform (GCP) is the core environment.

📝 Enhancement Note: The technology stack is heavily weighted towards front-end development within the Google ecosystem. The emphasis on "Python" as a primary language, alongside "TypeScript" and "Angular" for the front-end, gives candidates a clear picture of the technical requirements. BigQuery itself is a primary tool and subject of the role.

👥 Team Culture & Values

Operations Values:

• User Focus: Prioritizing the user experience to drive adoption and satisfaction with BigQuery.

• Innovation: Encouraging new ideas and approaches to solve complex UI and data analytics challenges.

• Collaboration: Fostering a team environment where diverse perspectives are valued and cross-functional teamwork is essential.

• Excellence: Striving for high quality in code, design, and execution, with a commitment to reliability and performance.

• Data-Driven: Using data and user feedback to inform decisions and measure impact.

• Impact: Focusing efforts on features and improvements that deliver significant value to users and Google Cloud.

Collaboration Style:

• Cross-Functional Integration: Engineers work closely with Product Managers and UX Designers from the initial ideation phase through to implementation and iteration.

• Open Communication: Encouraging direct and honest feedback, both in code reviews and team discussions.

• Shared Ownership: Pods often operate with a sense of shared responsibility for their product area, promoting collective problem-solving.

• Knowledge Sharing: A culture of sharing best practices, learnings, and insights across teams.

📝 Enhancement Note: Google's core values of innovation, user focus, and collaboration are likely deeply embedded within this team's culture. The "Adoption Pod" context suggests a strong emphasis on user onboarding and making complex technology accessible.

⚡ Challenges & Growth Opportunities

Challenges:

• Scalability & Performance: Building a UI that performs flawlessly for massive datasets and a large user base.

• Complexity of BigQuery: Translating the power and complexity of BigQuery into an intuitive and manageable user interface.

• Cross-Team Dependencies: Navigating dependencies with backend BigQuery teams and other GCP UI teams to ensure cohesive user experiences.

• Rapid Evolution: Keeping pace with the rapid advancements in cloud technology and user expectations in data analytics.

• User Adoption: Designing features that effectively onboard new users and drive deeper engagement with BigQuery.

Learning & Development Opportunities:

• Advanced UI/UX Techniques: Gaining expertise in modern front-end development patterns and user-centric design principles.

• Cloud Architecture: Deepening understanding of Google Cloud Platform, distributed systems, and data warehousing.

• Data Analytics Domain: Becoming an expert in the BigQuery product and the broader data analytics landscape.

• Technical Leadership: Opportunities to lead feature development, mentor junior engineers, and contribute to architectural decisions.

• Industry Exposure: Working on a flagship product within a leading cloud provider, offering exposure to cutting-edge technologies and best practices.

📝 Enhancement Note: The challenges are specific to developing a sophisticated UI for a powerful data analytics tool within a large cloud ecosystem. Growth opportunities are framed around deepening technical skills, expanding domain knowledge, and developing leadership capabilities within Google.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you had to debug a complex issue in a large codebase. What was your process?" (Focus on systematic debugging, root cause analysis, and impact assessment.)

• "How would you design a user interface for a new feature in BigQuery that helps users visualize query results in real-time?" (Focus on user needs, UI/UX principles, and technical feasibility. Be prepared to discuss trade-offs.)

• "Tell me about a project where you had to collaborate closely with non-engineers (e.g., Product Managers, Designers). How did you ensure alignment and successful delivery?" (Highlight communication, empathy, and compromise.)

• "How do you approach writing code that is maintainable and efficient for a large-scale application?" (Discuss coding standards, testing, design patterns, and performance considerations.) Company & Culture Questions:

• "Why are you interested in Google and specifically the BigQuery UI team?" (Research BigQuery, Google Cloud, and the company's mission. Connect your skills and interests to the team's goals.)

• "Describe a situation where you received critical feedback on your code or design. How did you respond?" (Focus on receptiveness to feedback and continuous improvement.)

• "What do you think makes a great user experience for a data analytics tool?" (Demonstrate understanding of user needs in this domain.) Portfolio Presentation Strategy:

• Code Walkthrough: Be ready to walk through a significant project from your portfolio. Explain the problem you were solving, your technical approach, key design decisions, and the outcome.

• Highlight Impact: Quantify the impact of your work where possible (e.g., improved performance, user adoption metrics, efficiency gains).

• Focus on Process: Explain your development process, including how you handled challenges, collaborated with others, and ensured code quality.

• Relevance: Tailor your portfolio examples to highlight skills most relevant to the role (e.g., JavaScript/TypeScript/Angular, Python, data structures, algorithms, front-end development).

📝 Enhancement Note: These questions and strategies are designed to help candidates anticipate the types of technical and behavioral inquiries they might face, emphasizing the need to showcase problem-solving skills, collaborative abilities, and a deep understanding of software development best practices within the context of Google's culture.

📌 Application Steps

To apply for this Software Engineer position:

• Submit your application through the official Google Careers portal link provided.

• Portfolio Customization: Curate your GitHub profile or personal website to prominently feature projects demonstrating your proficiency in Python, JavaScript/TypeScript, Angular, and your understanding of data structures and algorithms. Ensure READMEs are clear and code is well-documented.

• Resume Optimization: Tailor your resume to highlight relevant experience and skills, using keywords from the job description such as "Software development," "BigQuery," "Google Cloud," "TypeScript," "Angular," and "Data Structures." Quantify achievements whenever possible.

• Interview Preparation: Dedicate significant time to practicing coding challenges (LeetCode, HackerRank) and brushing up on system design principles. Prepare STAR method answers for behavioral questions and research BigQuery's functionalities.

• Company Research: Thoroughly research Google's mission, its cloud offerings, and the BigQuery product. Understand the team's focus on user adoption and the general culture of Google's engineering teams.

⚠️ Important Notice: This enhanced job description has been generated to provide comprehensive insights based on the provided data and industry standards for Software Engineering roles at Google. Applicants should verify all details directly with Google's recruitment team.