Sr Software Engineer

Sr Software Engineer Department: Engineering Team: Data Location: Hyderabad, India Type: Full-Time We are looking for a Senior Data Engineer to contribute to high-impact initiatives within the Payments Data Engineering team. In this critical role, you will design, build, and optimize data systems that support the scalability, accuracy, and compliance of our global payments infrastructure. You’ll work closely with cross-functional partners in Engineering, Product, Risk, and Compliance to transform complex financial and transactional data into reliable pipelines, actionable insights, and audit-ready datasets. The ideal candidate is a strong individual contributor who combines deep technical expertise with a pragmatic approach to solving real-world data challenges. You are comfortable navigating ambiguity, driving projects forward, and have a passion for improving payment systems through robust, high-quality data solutions. \-\-\-\- What the Candidate Will Do ---- Partner with engineers, analysts, and product managers to define technical solutions that support business goals Contribute to the architecture and implementation of distributed data systems and platforms Identify inefficiencies in data processing and proactively drive improvements in performance, reliability, and cost Serve as a thought leader and mentor in data engineering best practices across the organization \-\-\-\- Basic Qualifications ---- 7+ years of hands-on experience in software engineering with a focus on data engineering Proficiency in at least one programming language such as Python, Java, or Scala Strong SQL skills and experience with large-scale data processing frameworks (e.g., Apache Spark, Flink, MapReduce, Presto) Demonstrated experience designing, implementing, and operating scalable ETL pipelines and data platforms Proven ability to work collaboratively across teams and communicate technical concepts to diverse stakeholders \-\-\-\- Preferred Qualifications ---- Deep understanding of data warehousing concepts and data modeling best practices Hands-on experience with Ha