We are seeking a Senior Data Engineer to join a high-impact engineering initiative aimed at modernizing and unifying the global data ecosystem for a premier, global leader in digital payment acceptance solutions. In this role, you will play a key technical role within a dedicated Grid Dynamics squad, focusing on architecting and delivering a next-generation Data Platform leveraging Databricks on AWS, Medallion Architecture, and ClickHouse for low-latency analytics. You will combine strong hands-on development with end-to-end delivery ownership—driving data quality, establishing robust automated testing practices, and translating business requirements into scalable engineering solutions. Essential functions Design and build production-grade data pipelines and data platform components using Databricks on AWS, PySpark, Python, and SQL. Implement scalable Data Models based on the Medallion Architecture framework (Bronze, Silver, and Gold layers). Architect and optimize low-latency, real-time analytics data paths using ClickHouse. Drive engineering quality across the delivery process by building automated unit, integration, and data quality testing frameworks without relying on dedicated QA resources. Collaborate directly with client stakeholders and team leadership to refine backlog items, clarify requirements, and run technical discussions. Conduct design and code reviews to enforce system reliability, maintainability, and architectural standards. Provide pragmatic support and maintenance for a legacy Hadoop/Kafka reporting platform (~10% effort split) while supporting the strategic shift to the new platform. Qualifications 5+ years of commercial data engineering experience building, scaling, and maintaining enterprise data platforms. Strong hands-on experience with Databricks , Spark / PySpark , Python , and advanced SQL . Proven track record of designing data models and architectures using the Medallion Architecture pattern. Practical experience implementing high-volume, low-latency analytics solutions using ClickHouse . Solid engineering background in automated testing methodologies (unit, integration, and data quality validation) within data pipelines. Demonstrated capability to translate complex business needs into technical designs and clear backlog requirements. Would be a plus Practical experience within the AWS cloud ecosystem. Familiarity with real-time streaming architectures and frameworks such as Apache Kafka. Domain knowledge in payment processing, financial services, or merchant reporting systems. Conceptual or hands-on exposure to MLOps frameworks or integrating AI/ML workflows into Databricks platforms. We offer Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About us Grid Dynamics (

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GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in , supported by profound expertise and ongoing investment in , , , and . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.