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Company Overview : Infosys is a global leader in next-generation digital services and consulting. With over four decades of experience in managing the systems and workings of global enterprises, the company steers clients through their digital transformation journey. Operating across more than 50 countries, Infosys enables businesses to navigate their digital evolution by leveraging cloud, AI, and data-driven platforms to achieve unprecedented levels of performance and customer delight. Role Overview : As a Distinguished Engineer at Infosys in Bangalore, you will serve as a primary technical authority, shaping the architectural vision for large-scale enterprise systems. You will work closely with senior leadership, global clients, and cross-functional engineering teams to solve complex technical challenges that drive business transformation. This role is pivotal in bridging the gap between high-level business strategy and robust technical execution, ensuring that our software ecosystems remain scalable, secure, and future-ready in an increasingly competitive digital landscape. Key Responsibilities : - Architect and oversee the implementation of complex microservices-based ecosystems to ensure high availability and seamless integration across enterprise platforms. - Lead the design of distributed systems that handle massive data throughput, ensuring performance optimization and fault tolerance for mission-critical applications. - Integrate advanced Artificial Intelligence and Machine Learning models into existing software frameworks to automate processes and enhance decision-making capabilities. - Define and enforce enterprise-wide engineering standards and best practices to maintain code quality, security, and architectural integrity across global projects. - Mentor high-potential engineering talent and foster a culture of technical excellence, innovation, and continuous learning within the organization. - Collaborate with stakeholders to translate complex business requirements into scalable technical roadmaps that deliver measurable value to clients. Required Skillset : Enterprise Competencies : - Learning Agility : Stays current with rapidly evolving AI, data engineering, and cloud technologies; continuously embeds new knowledge into platform strategy and team practices. Understands and bridges both data and AI engineering disciplines, adapting quickly as these fields converge. - Customer Centricity : Ensures data platforms and pipelines are designed around the needs of internal teams, end users, and the business - delivering reliable, governed, and accessible data products. Communicates strategy and technical direction with empathy and clarity across all levels, from engineers to executives. - Tenacity / Persistence : Balances empathy with a strong delivery focus - drives teams to meet high standards with predictable outcomes even in complex, large-scale environments. Removes impediments, resolves conflicts constructively, and maintains momentum across multiple teams and workstreams without losing sight of the long-term platform vision. Required Qualifications : - 12+ years of experience in data engineering, database engineering, or platform engineering, including 5+ years in senior technical leadership roles. - Proven experience leading teams building large-scale data platforms in cloud environments. - Deep hands-on expertise with Big data ecosystems (Hadoop, Spark, Hive, HDFS, etc.), ETL/ELT tools (Informatica, DataStage), Relational & non-relational databases (Teradata, Oracle, SQL Server, DB2, Redshift, NoSQL), and Programming (SQL, Python, Spark, Scala, Java, shell scripting). - Strong experience with AWS data services (S3, Glue, Athena, RDS, Redshift, etc.). - Solid understanding of distributed systems, data architecture, and performance optimization. - Demonstrated ability to partner with senior stakeholders and influence across technology and business teams. - Hands-on experience with AI technologies; ability to understand and implement new advancements and articulate technical details to both engineering teams and executives. - Financial discipline - ability to manage budget and financial responsibilities at a team and platform level. Desired Qualifications : - Experience in financial services, with understanding of consumer and commercial banking data. - Experience supporting or enabling AI/ML and GenAI solutions, including feature pipelines and analytics platforms. - Familiarity with data visualization and BI tools (Tableau, Cognos, SAS). - Knowledge of responsible AI, data governance, and regulatory considerations in highly regulated environments. - Experience modernizing legacy data platforms into cloud-native architectures. - Executive speaking skills - ability to articulate strategy, challenge the status quo, and present to senior leadership and key stakeholders with confidence. - Experience working across or within highly collaborative .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.