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We are looking for an experienced Senior Data Engineer with strong expertise in Real-Time Streaming, Java, Apache Kafka, Apache Flink, and PySpark to build and operate high-performance, scalable streaming data platforms supporting enterprise Business Platforms and Risk & Compliance initiatives. The ideal candidate will have extensive experience designing and implementing real-time data pipelines, event-driven architectures, and distributed data processing systems capable of handling high-volume, low-latency data workloads. This role requires strong engineering expertise in modern data platforms, stream processing, and Big Data technologies while collaborating closely with architects, platform teams, and business stakeholders. Requirements Key Responsibilities Design, develop, and maintain scalable real-time data pipelines using Apache Kafka, Apache Flink, Java, and PySpark. Build high-throughput, low-latency streaming applications supporting enterprise-scale business and regulatory workloads. Develop event-driven data processing solutions using Kafka and modern streaming technologies. Design and implement distributed data processing pipelines for real-time analytics and operational reporting. Collaborate with Data Architects, Platform Engineering teams, Analytics teams, and Business stakeholders to understand requirements and deliver scalable data solutions. Develop reusable, secure, and maintainable data engineering components following enterprise engineering standards. Optimize streaming jobs for performance, scalability, fault tolerance, and reliability. Build and maintain batch and streaming ETL/ELT pipelines using PySpark. Monitor, troubleshoot, and resolve production issues within streaming data platforms. Participate in architecture discussions and contribute to the design of modern enterprise data platforms. Ensure data quality, governance, monitoring, logging, and operational excellence across streaming pipelines. Participate in Agile/Scrum ceremonies including sprint planning, backlog refinement, stand-ups, and retrospectives. Create technical documentation, implementation guides, and operational runbooks. Required Technical SkillsProgramming Strong hands-on experience with Java (Mandatory) Strong proficiency in Python Excellent understanding of Object-Oriented Programming (OOP) principles Real-Time Streaming Apache Kafka Apache Flink Kafka Streams Event-Driven Architecture Stream Processing Real-Time Data Engineering Big Data PySpark Apache Spark Distributed Data Processing Data Pipeline Development Databases SQL Relational Databases NoSQL databases (preferred) Data Engineering ETL/ELT Development Data Ingestion Data Transformation Data Integration Pipeline Orchestration Data Quality Performance Optimization Development & DevOps Git CI/CD pipelines Linux environment API Integration Monitoring & Logging tools Required Competencies Strong experience designing scalable distributed data systems. Excellent understanding of real-time streaming architectures. Ability to build secure, resilient, and fault-tolerant data pipelines. Strong analytical and problem-solving skills. Excellent communication and stakeholder management skills. Ability to work effectively in Agile delivery environments. Strong ownership mindset with focus on delivery quality and operational excellence. Ability to collaborate across cross-functional engineering and business teams. Preferred Experience Experience working on enterprise-scale data platforms. Exposure to Risk & Compliance or Business Platform data ecosystems. Experience supporting mission-critical, high-volume production environments. Knowledge of cloud-based data engineering platforms is an advantage. Experience with modern data architecture and distributed systems. Education Bachelor's or Master's Degree in Computer Science, Information Technology, Data Engineering, or a related field (or equivalent industry experience). Boolean Keywords (for better profile quality on job portals) Mandatory Skills: Java Apache Kafka Apache Flink PySpark Real-Time Streaming Data Engineering Event-Driven Architecture .
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.