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Senior Software Engineer Staff- Java

UKG

  • Noida, India
  • 70-80 Lacs PA
  • 12-18 Yrs
  • Posted Today
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About the role

We are seeking a highly skilled Senior Staff Software Engineer to join the engineering team for the Ready product. This role is ideal for a hands-on technologist who enjoys solving complex engineering problems, writing high-quality code, and building scalable, reliable, secure, and performant enterprise SaaS capabilities. As a Senior Staff Software Engineer, you will be a strong individual contributor and technical anchor for the team.

You will contribute directly to design and implementation, help shape the technology stack, support the technical roadmap, and partner with engineers, architects, product managers, and engineering leaders to deliver high-impact product capabilities. This role requires deep proficiency in Java, strong database technology experience, strong debugging and troubleshooting skills, and the ability to learn new technologies quickly. The ideal candidate is comfortable going deep into code, production behavior, performance bottlenecks, observability data, and system design while helping the team make sound technical decisions.

We are looking for an engineer with an enterprise-level mindset who can balance hands-on delivery with technical guidance, contribute to architecture discussions, improve engineering practices, and bring practical insight into AI-assisted engineering, agents, and intelligent automation. Responsibilities Hands-on Software Engineering Design, develop, test, and maintain high-quality backend services, APIs, distributed components, and cloud-native capabilities for the Ready product. Write clean, maintainable, performant, and well-tested code using Java and modern enterprise engineering practices.

Take ownership of complex technical deliverables from design through implementation, testing, release, and production support. Contribute to code reviews, design reviews, and engineering discussions with a focus on quality, simplicity, scalability, and maintainability. Quickly learn and apply new technologies, frameworks, tools, and platform capabilities as product and engineering needs evolve.

Technology Stack & Technical Roadmap Contribute to the evaluation, selection, and evolution of the technology stack for the Ready product, including application frameworks, database technologies, messaging, caching, observability, and cloud-native services. Partner with architects and engineering leaders to shape a practical technical roadmap that improves scalability, reliability, performance, developer productivity, and customer experience. Bring strong technical judgment to build-versus-buy decisions, framework selection, modernization efforts, and platform evolution.

Help translate product and business needs into sustainable technical designs and implementation plans. Architecture & Design Design scalable and resilient software components that align with enterprise SaaS architecture principles. Contribute to architecture discussions for distributed systems, microservices, APIs, event-driven workflows, data-intensive features, and integration patterns.

Identify design risks early and recommend pragmatic solutions that reduce complexity while supporting long-term product growth. Document technical designs, trade-offs, assumptions, and implementation approaches clearly for engineering teams. Observability, Troubleshooting & Operational Excellence Use observability platforms, logs, metrics, traces, dashboards, and alerts to understand system behavior and diagnose production issues.

Troubleshoot complex technical problems across application, database, infrastructure, integration, and deployment layers. Contribute to root-cause analysis, incident follow-ups, and reliability improvements that prevent recurring issues. Improve monitoring, telemetry, logging, and service health practices using tools such as OpenTelemetry, Grafana, Prometheus, Kibana, Datadog, Splunk, or similar platforms.

Support operational readiness through automation, meaningful alerts, clear runbooks, and production-aware engineering practices. Performance Engineering & Database Technology Tune application and database performance, including query optimization, indexing, connection management, caching, concurrency, transaction handling, and service-level latency improvements. Analyze performance bottlenecks using profiling, load testing, benchmarking, database execution plans, and production telemetry.

Design reliable and scalable data models using relational database technologies and appropriate data access patterns. Collaborate with teams to improve throughput, latency, resiliency, cost efficiency, and scalability of product services. AI-First Engineering & Agents Apply AI-assisted development tools to improve software design, coding, testing, documentation, troubleshooting, and developer productivity.

Bring practical understanding of AI trends, agents, coding assistants, and intelligent automation into engineering discussions. Identify opportunities where AI and agents can improve engineering workflows, support diagnostics, automate repetitive tasks, or enhance product capabilities. Follow responsible AI practices with attention to security, privacy, quality, reliability, and governance.

Technical Collaboration & Mentorship Collaborate closely with engineers, architects, product managers, quality engineers, SRE, and engineering leaders to deliver reliable product capabilities. Lead focused technical discussions when needed, especially around design choices, implementation approaches, troubleshooting, and performance improvements. Mentor engineers through code reviews, design feedback, debugging support, and sharing of engineering best practices.

Influence team-level engineering quality through strong hands-on contribution, technical credibility, and practical guidance.

Minimum Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. 10+ years of professional software engineering experience, including experience building enterprise-scale software products.
  • Strong hands-on proficiency in Java, backend service development, object-oriented design, concurrency, performance tuning, and modern Java frameworks.
  • Strong experience with database technologies, SQL, schema design, indexing, query optimization, transaction management, and database performance troubleshooting.
  • Experience designing and developing distributed systems, microservices, REST APIs, event-driven components, and cloud-native applications.
  • Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
  • Strong understanding of observability, monitoring, logging, tracing, metrics, alerting, and production diagnostics.
  • Experience troubleshooting complex technical issues across application, database, infrastructure, and integration layers.
  • Strong understanding of performance engineering, including profiling, load testing, caching, query tuning, and scalability analysis.
  • Ability to learn new technologies quickly and apply them effectively in production-grade software development.
  • Practical understanding of AI-assisted engineering tools, AI agents, and emerging automation capabilities.
  • Strong communication, collaboration, problem-solving, and mentoring skills.

Preferred Qualifications

  • Experience working on large-scale enterprise SaaS products serving global customers.
  • Experience contributing to technical roadmaps, platform modernization, cloud transformation, or technology stack evolution.
  • Experience with Kubernetes, containers, CI/CD pipelines, DevOps practices, and Infrastructure as Code.
  • Hands-on experience with observability tools such as OpenTelemetry, Grafana, Prometheus, Kibana, Splunk, Datadog, or similar platforms.
  • Experience with distributed caching, messaging platforms, asynchronous processing, and event-driven architecture.
  • Strong understanding of secure software development, authentication, authorization, data protection, and enterprise integration patterns.
  • Experience using AI coding assistants, engineering agents, intelligent automation, or AI-enabled operational tooling.
  • Demonstrated ability to mentor engineers while remaining deeply hands-on in design, coding, debugging, and delivery.
  • Key Attributes Strong hands-on developer who is ready to write code and solve hard technical problems.
  • Fast learner who can evaluate and adopt new technologies pragmatically.
  • Production-minded engineer with strong focus on reliability, observability, scalability, performance, and security.
  • Practical technical leader who influences through code quality, engineering judgment, and collaboration.
  • Comfortable troubleshooting deep technical issues and driving them to resolution.
  • Curious and forward-looking engineer with strong interest in AI-first development and agent-based automation

Eligibility & process

Who can apply

Experience: 12-18 Yrs. Open to matching qualifications.

Skills & stack

Spring Boot Boot Saas Product Development Java SQL REST APIs Microservices AWS

Selection process

  1. Online Assessment / Technical Interview Rounds / HR Review

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Spring Boot, Boot, Saas Product Development, Java, SQL, REST APIs, Microservices, AWS) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion UKG Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join UKG as a Senior Software Engineer Staff- Java?
Highlight UKG's market reputation, recent tech innovations, and how your skills in Spring Boot directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
UKG 70-80 Lacs PA
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