Senior Software Engineer ( UI Backend and Data Pipeline Engineer)

📍 Job Overview

Job Title: Senior Software Engineer (UI Backend and Data Pipeline Engineer)

Company: S&P Global

Location: Sadaramangala, Karnataka, India

Job Type: FULL_TIME

Category: Data Engineering / Software Engineering

Date Posted: 2025-10-03

Experience Level: 7+ years of experience

Remote Status: On-site

🚀 Role Summary

• Design, develop, and maintain scalable cloud-native solutions, with a strong emphasis on AWS services for data pipelines and backend systems.

• Build and optimize robust UI backend services, ensuring high performance, responsiveness, and data integrity through rigorous validation.

• Drive innovation in data product development for the automotive industry, leveraging advanced analytics and cutting-edge technologies to deliver forecasting solutions.

• Collaborate closely with data scientists, analysts, and cross-functional teams to define data requirements, optimize data flow, and enhance data storage for analytical purposes.

• Mentor junior engineers, lead data integration projects, and champion software development best practices to ensure timely and high-quality delivery.

📝 Enhancement Note: While the job title includes "Software Engineer," the detailed responsibilities and required skills heavily lean into Data Engineering and Backend Development with a focus on cloud infrastructure (AWS). The role is categorized as such to better attract operations-minded candidates who focus on data pipelines, system integration, and backend logic supporting analytical functions, rather than pure front-end UI development.

📈 Primary Responsibilities

• Design, develop, and maintain scalable and complex data pipelines, ensuring efficient data ingestion, transformation, and loading processes.

• Construct and manage responsive and high-performance UI backend services using languages such as Python, C#, or equivalent object-oriented programming paradigms.

• Implement and enforce robust data quality and integrity checks throughout all stages of the data pipeline and backend services.

• Develop and maintain a strong understanding of data integration methodologies and data modeling techniques to support analytical needs.

• Lead data integration initiatives, providing technical guidance and mentorship to junior engineering staff.

• Actively collaborate with cross-functional teams, including product managers, data scientists, and analysts, to define and translate data requirements into technical specifications.

• Work in tandem with data scientists and analysts to refine data flow architectures and optimize data storage solutions for advanced analytical workloads.

• Take full ownership of assigned modules, ensuring on-time delivery, adherence to quality standards, and implementation of software development best practices.

• Strategically utilize Redis for caching mechanisms and data storage solutions to significantly enhance application performance and user experience.

📝 Enhancement Note: The responsibilities highlight a blend of core data engineering (pipelines, quality, integration, modeling) and backend development (services, performance, caching). The emphasis on collaboration with data scientists and analysts positions this role as a key enabler of advanced analytics and forecasting within the S&P Mobility segment, aligning it closely with GTM operations enablement.

🎓 Skills & Qualifications

Education:

Experience:

• A minimum of 7 years of progressive experience in Data Engineering, Advanced Analytics, or a related backend development capacity.

Required Skills:

• Data Engineering Proficiency: Strong expertise in designing, building, and maintaining scalable data pipelines, including complex algorithmic processing.

• Backend Development: Proficiency in Python and experience with frameworks like Flask for building efficient backend services.

• Object-Oriented Programming (OOP): Solid understanding and practical application of OOP principles.

• Data Management: Extensive experience with SQL and data warehousing concepts, including data modeling and data manipulation libraries (e.g., Pandas, Polars, NumPy).

• Cloud Fundamentals: Foundational knowledge of cloud platforms, with a strong emphasis on data-centric AWS services.

• Data Quality & Integration: Proven ability to ensure data quality, integrity, and effective data integration.

• Problem-Solving: Excellent analytical and problem-solving skills with a knack for identifying and resolving complex technical challenges.

• Collaboration: Demonstrated ability to work effectively in cross-functional teams and collaborate with technical and non-technical stakeholders.

Preferred Skills:

• AWS Ecosystem: Hands-on experience with key AWS services such as ECR, Containerization (e.g., Docker), Batch, Step Functions, DynamoDB, and Lambda.

• Caching Solutions: Experience utilizing Redis for caching and performance optimization.

• CI/CD: Familiarity with GitLab CI/CD or similar tools for continuous integration and deployment automation.

• Mentorship: Experience in leading projects and mentoring junior engineers.

📝 Enhancement Note: The requirements blend core software engineering with specialized data engineering and cloud skills. The "7+ years" experience level suggests this is a senior individual contributor role with potential for technical leadership and mentorship, fitting well within a GTM or RevOps context where robust data infrastructure is critical. The preference for specific AWS services and tools like Redis and GitLab CI/CD indicates a modern, cloud-native development environment.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase of end-to-end data pipeline projects, detailing design, implementation, and maintenance phases.

• Examples of backend services developed, highlighting performance metrics, scalability considerations, and problem-solving approaches.

• Case studies demonstrating data quality assurance processes and data integrity improvements implemented.

• Projects illustrating effective data integration strategies and data modeling techniques applied to solve business problems.

Process Documentation:

• Demonstrate ability to document complex data pipelines, including data flow diagrams, transformation logic, and validation rules.

• Provide examples of how you've documented backend service APIs, configurations, and deployment processes.

• Showcase experience in creating and maintaining documentation for data quality checks and remediation procedures.

• Illustrate how you've documented data models and their relationships within a data warehouse or data lake environment.

📝 Enhancement Note: For a senior role like this, a portfolio is crucial. It should not only showcase technical outputs but also the candidate's thought process, problem-solving capabilities, and understanding of best practices in data engineering and backend development. Emphasis should be placed on quantifiable results and the impact of their work on data availability, quality, and system performance, which are critical for GTM operations.

💵 Compensation & Benefits

Salary Range:

The estimated salary range for a Senior Software Engineer (UI Backend and Data Pipeline Engineer) in Bangalore, India, with 7+ years of experience, typically falls between ₹18,00,000 to ₹30,00,000 per annum. This range can vary based on specific skills, interview performance, and S&P Global's internal compensation structure.

Benefits:

S&P Global offers a comprehensive benefits package designed to support employees' well-being, financial security, and professional growth. These include:

• Health & Wellness: Robust health coverage options for physical and mental well-being.

• Flexible Downtime: Generous paid time off (PTO) and holidays to encourage work-life balance.

• Continuous Learning: Access to extensive resources for professional development, including training programs, courses, and potentially certifications.

• Invest in Your Future: Competitive salary, retirement planning options, and a continuing education program with company-matched student loan contributions.

• Family Friendly Perks: Benefits designed to support employees with families, including potential parental leave and childcare assistance programs.

• Beyond the Basics: Various perks such as retail discounts and employee referral incentives.

Working Hours:

The standard working hours for this full-time role are typically 40 hours per week. While the role is on-site, S&P Global may offer some flexibility within core business hours, depending on team needs and project demands, to accommodate efficient work execution and collaboration.

📝 Enhancement Note: Salary ranges for senior engineering roles in Bangalore are competitive. The provided estimate is based on industry benchmarks for experienced engineers in a major tech hub like Bangalore, considering the demand for specialized skills in cloud, data engineering, and backend development. The benefits listed are directly from the job description and are tailored to appeal to experienced professionals seeking a stable and supportive work environment.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Information Services and Data Analytics, with a significant focus on the Automotive sector through S&P Global Mobility.

Company Size: S&P Global is a large, publicly traded corporation with over 35,000 employees globally. This Senior Software Engineer role is within the S&P Mobility segment, which is planned to become a standalone public company.

Founded: S&P Global traces its roots back to 1860, with continuous evolution and strategic acquisitions leading to its current form.

Team Structure:

• The S&P Mobility technology team is comprised of "mighty engineers" focused on developing new, highly visible, and strategic products.

• This role is expected to be part of a team that includes data scientists and analysts, fostering a collaborative environment where technical expertise directly supports business strategies.

• The reporting structure likely involves a Tech Lead or Engineering Manager, with opportunities for mentorship and technical guidance to junior team members.

Methodology:

• Data-Driven Innovation: Emphasis on leveraging data to create competitive advantages and drive business growth through advanced analytics and forecasting solutions.

• Cloud-Native Development: Focus on building scalable, modern solutions utilizing AWS cloud infrastructure.

• Agile Development Practices: Implicitly, the fast-paced, collaborative environment suggests adherence to agile methodologies for iterative development and rapid deployment.

• Continuous Improvement: Demonstrated through the use of CI/CD pipelines and a focus on software development best practices, aiming for ongoing optimization of data pipelines and backend services.

Company Website: https://www.spglobal.com/ and specifically for Mobility: http://www.spglobal.com/mobility

📝 Enhancement Note: S&P Global is a well-established, large-scale enterprise with a strong reputation. The S&P Mobility segment is undergoing a strategic separation, indicating an environment of growth and transformation. For an operations professional, this means working within a structured organization that values data-driven insights and advanced technology, with the potential for significant impact on a specialized market. The culture likely balances established corporate practices with a drive for innovation in its product offerings.

📈 Career & Growth Analysis

Operations Career Level: This is a Senior Software Engineer role, indicating a highly experienced individual contributor. In an operations context, this role is critical for building and maintaining the technical infrastructure that supports data-driven decision-making, GTM strategy execution, and revenue enablement. The responsibilities suggest a deep technical focus with the ability to influence technical direction and mentor others.

Reporting Structure: The role likely reports to an Engineering Manager or Tech Lead within the S&P Mobility technology team. Collaboration will be extensive with data scientists, analysts, product managers, and other engineers, forming a matrixed operational structure common in large tech organizations.

Operations Impact: This role has a direct impact on the core business of S&P Mobility by enabling the development of automotive forecasting solutions. By building robust data pipelines and backend services, the engineer provides the essential intelligence that clients rely on for strategic business decisions. This directly supports revenue generation by enhancing the value and accuracy of S&P Global's data products.

Growth Opportunities:

• Technical Specialization: Deepen expertise in AWS cloud-native services, data pipeline architecture, and backend development for analytical applications.

• Leadership & Mentorship: Opportunity to lead technical initiatives, mentor junior engineers, and contribute to architectural decisions.

• Cross-Functional Exposure: Gain exposure to product development, data science methodologies, and business strategy within the automotive industry.

• Potential for Future Leadership: As S&P Mobility becomes a standalone entity, there may be opportunities for advancement into technical team lead or management roles.

• Continuous Learning: Access to company-provided learning resources, encouraging ongoing skill development in emerging technologies relevant to data engineering and cloud computing.

📝 Enhancement Note: For operations professionals, this role represents an opportunity to work at the intersection of technology and business intelligence within a specialized industry. The growth path is geared towards deepening technical expertise and potentially moving into leadership roles, impacting core business operations and revenue enablement through robust data infrastructure.

🌐 Work Environment

Office Type: The role is designated as on-site, suggesting a traditional office environment within S&P Global's Bangalore location.

Office Location(s): The primary location is Sadaramangala, Karnataka, India. This implies working from a physical S&P Global office in the Bangalore metropolitan area.

Workspace Context:

• Collaborative Environment: The job description emphasizes collaboration with cross-functional teams, suggesting an open or semi-open office layout conducive to team interaction.

• Technology-Rich: As a technology-focused role within a major corporation, expect access to modern development tools, high-performance computing resources, and robust network infrastructure.

• Team Interaction: Opportunities for direct interaction with colleagues in engineering, data science, and product management, fostering knowledge sharing and problem-solving.

• Focus on Innovation: The team is described as developing new products and leveraging cutting-edge technology, indicating an environment that encourages forward-thinking and creative solutions.

Work Schedule: Standard full-time working hours (approximately 40 hours per week) are expected, with an on-site presence. While flexibility may exist within core hours, the emphasis is on consistent availability for team collaboration and project deadlines.

📝 Enhancement Note: An on-site role in a major tech hub like Bangalore suggests a dynamic work environment with opportunities for direct collaboration and access to corporate resources. For operations roles, this can mean better integration with internal teams and a clearer understanding of day-to-day business processes and challenges.

📄 Application & Portfolio Review Process

Interview Process:

The interview process for a Senior Software Engineer role at S&P Global typically involves several stages designed to assess technical expertise, problem-solving skills, and cultural fit:

1. Initial Screening: An HR or recruiter screen to assess basic qualifications, experience, and interest in the role.

2. Technical Screening: An online coding assessment or a technical phone interview focusing on data structures, algorithms, and core programming concepts (e.g., Python, OOP).

3. On-site/Virtual Interviews: Multiple rounds of interviews, potentially including:

• System Design Interview: Evaluating the ability to design scalable and robust systems, focusing on data pipelines, backend architecture, and cloud services.
• Coding/Problem-Solving Session: Deeper dives into coding challenges, potentially related to data manipulation, algorithm optimization, or backend logic.
• Behavioral Interview: Assessing soft skills, leadership potential, collaboration style, and alignment with S&P Global's values (Integrity, Discovery, Partnership).
• Domain-Specific Interview: Discussions related to data engineering, AWS, and potentially automotive industry insights, if applicable.

1. Hiring Manager/Team Lead Interview: A final discussion to gauge overall fit, discuss career aspirations, and answer candidate questions.

Portfolio Review Tips:

• Highlight Impact: For each project in your portfolio, clearly articulate the problem statement, your specific contributions, the technologies used, and the quantifiable impact (e.g., performance improvements, cost savings, data accuracy gains, faster insights).

• Showcase Process: Detail the design and development process, including challenges faced, solutions implemented, and lessons learned. For data pipelines, illustrate the flow, transformations, and quality checks. For backend services, show API designs, error handling, and caching strategies.

• AWS Proficiency: If you have AWS experience, explicitly showcase projects that leverage services like ECR, Lambda, DynamoDB, Step Functions, etc. Demonstrate an understanding of cloud-native principles.

• Code Quality: Ensure any code samples are well-documented, follow best practices (e.g., PEP 8 for Python), and are easily navigable.

• Tailor to Role: Emphasize projects that align with the core requirements: scalable data pipelines, Python/Flask backend services, data quality, and AWS.

Challenge Preparation:

• Practice Coding: Be prepared for live coding challenges on platforms like HackerRank or LeetCode, focusing on data structures, algorithms, and Python.

• System Design Scenarios: Practice designing distributed systems, data pipelines, and APIs. Consider scalability, reliability, performance, and cost-effectiveness.

• AWS Knowledge: Brush up on core AWS services relevant to data engineering and backend development. Understand concepts like serverless computing, containerization, and managed databases.

• Behavioral Questions: Prepare STAR method (Situation, Task, Action, Result) responses for common behavioral questions related to teamwork, problem-solving, leadership, and handling challenges.

• Understand S&P Mobility: Research the S&P Mobility segment, its products, and its role in the automotive industry. Understand how data and analytics drive its business.

📝 Enhancement Note: The interview process is rigorous, as expected for a senior role at a large corporation. A strong portfolio demonstrating tangible results and a solid understanding of cloud-native development and data engineering principles will be critical for success. Candidates should be prepared to discuss technical details and demonstrate problem-solving abilities under pressure.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Python (primary), C# (potential alternative)

• Backend Frameworks: Flask (preferred for Python)

• Caching/Data Storage: Redis (explicitly mentioned for performance)

• Databases: SQL (required), DynamoDB (preferred AWS service)

• Data Manipulation Libraries: Pandas, Polars, NumPy

• Cloud Platform: AWS (significant emphasis)

• Containerization: ECR, Docker (implied by containerization)

• AWS Services: Batch, Step Functions, Lambda (preferred)

• Version Control: GitLab (implied by GitLab CI/CD)

Analytics & Reporting:

CRM & Automation:

• Not directly mentioned as part of this role's primary stack, but understanding how data pipelines feed into CRM or other operational systems would be beneficial.

📝 Enhancement Note: This role is heavily focused on a modern, cloud-native technology stack. Proficiency in Python, AWS services, and data manipulation libraries is essential. The mention of Redis highlights a focus on performance optimization, a key aspect for backend services supporting data-intensive operations. Experience with CI/CD tools like GitLab is also a strong indicator of the team's development practices.

👥 Team Culture & Values

Operations Values:

S&P Global's core values are Integrity, Discovery, and Partnership. For this role, these translate to:

• Integrity: Ensuring the accuracy, reliability, and security of data pipelines and backend services, upholding the trust clients place in S&P Global's "Essential Intelligence."

• Discovery: A spirit of curiosity and innovation, actively seeking new ways to leverage data, develop advanced analytics, and build cutting-edge cloud-native solutions for the automotive market.

• Partnership: Collaborating effectively with internal teams (data scientists, product managers, analysts) and potentially external stakeholders to achieve shared goals and deliver impactful solutions.

Collaboration Style:

• Cross-Functional Integration: The role requires close collaboration, bridging the gap between backend development, data engineering, and data science/analytics functions.

• Mentorship and Knowledge Sharing: As a senior engineer, there's an expectation to share knowledge, guide junior team members, and contribute to a culture of continuous learning.

• Agile and Responsive: Working in a fast-paced environment suggests an agile approach to development, with regular feedback loops and adaptability to changing requirements.

• Data-Centric Problem Solving: Decisions and solutions are expected to be driven by data and analytical insights, with a focus on delivering measurable business value.

📝 Enhancement Note: The emphasis on core values like Integrity and Partnership is crucial for operations roles where trust, collaboration, and ethical data handling are paramount. The "Discovery" value aligns with the innovative nature of the role, driving new product development in the automotive forecasting space.

⚡ Challenges & Growth Opportunities

Challenges:

• Scalability and Performance: Designing and maintaining data pipelines and backend services that can handle large volumes of data and high traffic without performance degradation.

• Data Complexity: Working with complex datasets and developing sophisticated algorithms for accurate automotive forecasting.

• Cloud Architecture Evolution: Staying abreast of rapidly evolving AWS services and best practices to ensure optimal and cost-effective cloud-native solutions.

• Cross-Functional Alignment: Effectively translating diverse requirements from product, data science, and business teams into robust technical solutions.

• Mentoring Junior Engineers: Balancing individual contributions with the responsibility of guiding and developing less experienced team members.

Learning & Development Opportunities:

• Advanced AWS Training: Deepen expertise in specialized AWS services relevant to data engineering and backend development, potentially leading to certifications.

• Data Science Collaboration: Gain exposure to advanced analytics, machine learning models, and forecasting techniques used by data scientists.

• Automotive Market Insights: Develop a strong understanding of the automotive industry, its trends, and the data that drives its market dynamics.

• Technical Leadership: Opportunities to take on technical leadership roles in projects, influence architectural decisions, and contribute to strategic technology planning.

• Exposure to New Tools: Potential to work with emerging data processing and analytical frameworks.

📝 Enhancement Note: The challenges presented are typical for senior roles in data-intensive, cloud-focused environments. The growth opportunities are significant, offering a path for deep technical specialization, leadership development, and valuable industry-specific knowledge acquisition, which can be highly beneficial for operations professionals aiming to enhance their strategic impact.

💡 Interview Preparation

Strategy Questions:

• Data Pipeline Design: Be prepared to discuss how you would design a scalable data pipeline for ingesting and processing real-time automotive sales data, considering data quality, transformations, and storage for forecasting.

• Backend Service Architecture: Explain how you would design a Python/Flask backend service to serve API requests for automotive market trends, focusing on performance, caching (Redis), and scalability on AWS.

• AWS Service Selection: Justify your choice of AWS services (e.g., Lambda, Step Functions, DynamoDB, ECR) for specific data processing or backend tasks, detailing trade-offs and best practices.

• Data Quality & Integrity: Describe your approach to ensuring data quality and integrity in large-scale data pipelines, including validation strategies and error handling.

Company & Culture Questions:

• Alignment with Values: Provide examples of how you've demonstrated Integrity, Discovery, and Partnership in your previous roles, especially in technical or collaborative settings.

• Handling Ambiguity: Discuss how you approach projects with unclear requirements or evolving technical landscapes, common in fast-paced innovation environments.

• Teamwork and Mentorship: Share experiences of collaborating with diverse teams (engineers, data scientists, analysts) and how you've mentored junior colleagues.

• Impact on Business: How do you ensure your technical work directly contributes to business objectives and provides "Essential Intelligence" to clients?

Portfolio Presentation Strategy:

• Quantify Impact: For each project, clearly state the business problem, your solution, the technologies used, and the measurable outcomes (e.g., "Reduced data processing time by 30%," "Improved forecast accuracy by 5%," "Enabled real-time analytics for X users").

• Tell a Story: Structure your portfolio presentation as a narrative, guiding the interviewer through the problem, your thought process, the technical implementation, and the successful resolution.

• Focus on Key Technologies: Highlight your proficiency in Python, Flask, AWS services, Redis, SQL, and data manipulation libraries, demonstrating how you've applied them effectively.

• Showcase Problem-Solving: Be ready to deep-dive into specific technical challenges you faced and how you overcame them, demonstrating your analytical and problem-solving skills.

• Prepare for Q&A: Anticipate questions about your design choices, trade-offs considered, and alternative approaches.

📝 Enhancement Note: Preparation should focus on demonstrating not just technical proficiency but also strategic thinking, problem-solving skills, and an understanding of how technology drives business outcomes. The portfolio is a critical asset for showcasing tangible achievements and should be presented with a clear focus on impact and technical depth.

📌 Application Steps

To apply for this Senior Software Engineer position:

• Submit your application through the S&P Global careers portal via the provided URL.

• Resume Optimization: Tailor your resume to highlight experience in Python, Flask, AWS, data pipeline development, and backend services. Quantify achievements with metrics wherever possible, using keywords from the job description such as "scalable data pipelines," "UI backend services," "AWS proficiency," and "data quality."

• Portfolio Preparation: Curate a portfolio that showcases relevant projects. Focus on end-to-end data pipeline implementations, backend service development, and any experience with cloud-native AWS solutions. Be prepared to discuss your contributions, the technologies used, and the impact of your work with specific examples.

• Technical Skill Refresher: Review core concepts in Python, object-oriented programming, SQL, data structures, algorithms, and common AWS services (ECR, Lambda, DynamoDB, Step Functions). Practice coding challenges and system design scenarios.

• Company Research: Familiarize yourself with S&P Global, its mission, and specifically the S&P Mobility segment. Understand their role in the automotive industry and the importance of data-driven insights. Research their stated values (Integrity, Discovery, Partnership) and consider how your experience aligns.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.