Senior Big Data Engineer (Python + AWS)

🏢 Summary: Opportunity for an experienced Big Data Engineer to design and optimize a high-performance data analytics platform processing petabyte-scale datasets. The role focuses on building robust data pipelines, scalable workflows, and real-time reporting systems using modern Big Data technologies. You will work on performance tuning, data quality, and reliable large-scale data processing solutions. 🗂️ Requirements: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, Proven experience as Data Engineer or similar role, Strong proficiency in Spark, HDFS, Airflow, Solid programming skills in Scala, Experience designing and implementing data pipelines, Experience building continuous reporting systems and dashboards, Knowledge of data warehousing concepts, Ability to optimize and tune data processing systems 📃 Skills: Scala, Spark, HDFS, Airflow, Gradle, Kubernetes, BigData, ETL, DataWarehousing, CI/CD 🏢 Description: Our customer is one of the world’s largest technology companies based in Silicon Valley with operations all over the world. In this project, we are working on the bleeding edge of Big Data technology to develop a high-performance data analytics platform, which handles petabytes datasets. We are looking for an experienced Big Data Engineer. Essential functions Design, develop, and maintain robust data pipelines using: Scala, Spark, HDFS, Gradle, Kubernetes and Airflow Implement scalable and efficient data workflows to support data ingestion, processing, and analysis. Develop and maintain continuous reporting systems and dashboards to provide real-time insights. Collaborate with cross-functional teams to understand data requirements and deliver data solutions. Optimize and tune data processing systems for performance and reliability. Ensure data quality and integrity throughout the data lifecycle. Troubleshoot and resolve data processing and pipeline issues. Stay up-to-date with industry trends and emerging technologies to drive innovation in data engineering. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience as a Data Engineer or in a similar role. Strong proficiency in Spark, HDFS, Airflow Solid programming skills in Scala. Experience with data pipeline architecture and implementation. Expertise in building and maintaining continuous reporting systems and dashboards. Familiarity with data warehousing concepts and technologies. Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills. Would be a plus DevOps/CICD skills 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 (NASDAQ: 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 enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: The offer is for an experienced Big Data Engineer to design and maintain a high-performance data analytics platform processing petabyte-scale datasets. The role focuses on building scalable data pipelines, optimizing distributed processing systems, and delivering real-time reporting solutions using modern Big Data technologies. The position involves close collaboration with cross-functional teams to ensure reliable, high-quality data workflows. 🗂️ Requirements: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, Proven experience as a Data Engineer or similar role, Strong proficiency in Spark, HDFS, Airflow, Strong programming skills in Scala, Experience with data pipeline architecture and implementation, Experience building continuous reporting systems and dashboards, Familiarity with data warehousing concepts, Ability to optimize and tune distributed data processing systems 📃 Skills: Scala, Spark, HDFS, Airflow, Gradle, Kubernetes, BigData, DataWarehousing, CI/CD 🏢 Description: Our customer is one of the world’s largest technology companies based in Silicon Valley with operations all over the world. In this project, we are working on the bleeding edge of Big Data technology to develop a high-performance data analytics platform, which handles petabytes datasets. We are looking for an experienced Big Data Engineer. Essential functions Design, develop, and maintain robust data pipelines using: Scala, Spark, HDFS, Gradle, Kubernetes and Airflow Implement scalable and efficient data workflows to support data ingestion, processing, and analysis. Develop and maintain continuous reporting systems and dashboards to provide real-time insights. Collaborate with cross-functional teams to understand data requirements and deliver data solutions. Optimize and tune data processing systems for performance and reliability. Ensure data quality and integrity throughout the data lifecycle. Troubleshoot and resolve data processing and pipeline issues. Stay up-to-date with industry trends and emerging technologies to drive innovation in data engineering. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience as a Data Engineer or in a similar role. Strong proficiency in Spark, HDFS, Airflow Solid programming skills in Scala. Experience with data pipeline architecture and implementation. Expertise in building and maintaining continuous reporting systems and dashboards. Familiarity with data warehousing concepts and technologies. Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills. Would be a plus DevOps/CICD skills 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 (NASDAQ: 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 enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: The offer is for an experienced Big Data Engineer to design and maintain a high-performance data analytics platform processing petabyte-scale datasets. The role focuses on building scalable data pipelines, optimizing distributed systems, and delivering real-time reporting solutions using modern Big Data technologies. You will work on cutting-edge data engineering challenges in a large-scale, global environment. 🗂️ Requirements: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, Proven experience as Data Engineer or similar role, Strong proficiency in Spark, HDFS, Airflow, Strong programming skills in Scala, Experience with data pipeline architecture and implementation, Experience building continuous reporting systems and dashboards, Knowledge of data warehousing concepts, Ability to optimize and tune distributed data systems, Experience ensuring data quality and integrity, Ability to troubleshoot complex data pipeline issues 📃 Skills: Scala, Spark, HDFS, Airflow, Gradle, Kubernetes, BigData, ETL, DataWarehousing, Dashboards 🏢 Description: Our customer is one of the world’s largest technology companies based in Silicon Valley with operations all over the world. In this project, we are working on the bleeding edge of Big Data technology to develop a high-performance data analytics platform, which handles petabytes datasets. We are looking for an experienced Big Data Engineer. Responsibilities: Design, develop, and maintain robust data pipelines using: Scala, Spark, HDFS, Gradle, Kubernetes and Airflow Implement scalable and efficient data workflows to support data ingestion, processing, and analysis. Develop and maintain continuous reporting systems and dashboards to provide real-time insights. Collaborate with cross-functional teams to understand data requirements and deliver data solutions. Optimize and tune data processing systems for performance and reliability. Ensure data quality and integrity throughout the data lifecycle. Troubleshoot and resolve data processing and pipeline issues. Stay up-to-date with industry trends and emerging technologies to drive innovation in data engineering. Requirements : Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience as a Data Engineer or in a similar role. Strong proficiency in Spark, HDFS, Airflow Solid programming skills in Scala. Experience with data pipeline architecture and implementation. Expertise in building and maintaining continuous reporting systems and dashboards. Familiarity with data warehousing concepts and technologies. Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills. Ability to work independently and in a remote team environment. 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 (NASDAQ: 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 enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Senior Python Engineer role focused on building scalable, secure backend systems and infrastructure for a machine learning platform in a global fintech environment. The position centers on developing production-grade services, real-time data pipelines, and cloud-native platform capabilities that enable ML model deployment and monitoring. The role supports low-latency, high-availability systems such as fraud detection. 🗂️ Requirements: Strong commercial experience building production-grade backend systems in Python, Experience designing and operating distributed systems, Practical experience with AWS services (EKS, S3, Lambda), Experience with Docker and Kubernetes, Experience with databases, data pipelines, or streaming platforms, Knowledge of testing methodologies and CI/CD practices, Ability to work in high-availability, regulated environments 📃 Skills: Python, FastAPI, Microservices, DistributedSystems, AWS, EKS, S3, Lambda, Docker, Kubernetes, Kafka, Flink, Databases, Streaming, CICD, GitOps, GitHub, ArgoCD, Datadog, Observability 🏢 Description: We are looking for a Senior Python Engineer to join our ML Platform team. You will be responsible for building the backend systems and infrastructure that power machine learning across a global fintech project. This is a platform engineering role focused on building scalable, reliable, and secure systems that enable ML engineers and data scientists to develop, deploy, and operate models in production. Your work will directly support low-latency, real-time environments, such as fraud detection. Please note: Prior Machine Learning experience is NOT required! If you are a strong backend engineer with an interest in data-driven platforms and ML systems, this is the perfect role for you. Responsibilities: Backend Development: Design and build production-grade Python services (FastAPI / microservices) that support the ML lifecycle, including feature computation, model inference, and monitoring. Real-Time Data Pipelines: Develop and operate data pipelines to support low-latency, high-availability use cases (like fraud detection) using event-driven architectures (Kafka, Flink). Platform Engineering: Build capabilities to enable online and offline feature stores, working closely with Data Engineering to ensure reliable data flows. Developer Experience (DevEx): Improve the daily lives of ML engineers and data scientists through better tooling, automation, and self-service APIs. Cloud & DevOps: Build and maintain CI/CD pipelines (GitOps, GitHub Actions, ArgoCD) and ensure the observability (Datadog), resilience, and scalability of platform services. Security & Compliance: Collaborate with Infrastructure and Security teams to ensure all systems meet strict financial and regulatory standards. Min requirements: Python Mastery: Strong commercial experience in building production-grade backend systems and microservices in Python (this is not a scripting role). Distributed Systems: Proven experience designing, building, and operating backend services or distributed systems. Cloud & Containerization: Solid practical experience with AWS (EKS, S3, Lambda) and container orchestration ( Docker, Kubernetes ). Data Systems: Experience working with databases, data pipelines, or streaming platforms. Engineering Best Practices: Solid understanding of testing methodologies, CI/CD, and code quality standards. High-Availability Focus: Ability to work in highly regulated, high-availability environments where system resilience is critical. Would be a plus: Experience with real-time streaming technologies (Kafka, Flink) and low-latency systems. Background in fintech, payments, risk systems, or fraud detection. Experience with ML platforms/tools (e.g., SageMaker, Ray, Tecton) or exposure to feature stores (online/offline architectures). A general understanding of the machine learning lifecycle (training, inference, feature engineering). 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 (NASDAQ: 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 enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Senior DevOps Engineer role focused on ensuring production stability and driving automation across multi-cloud environments. The position bridges infrastructure and application support, emphasizing CI/CD optimization, incident management, and elimination of manual operational tasks. Responsibilities include managing deployments, patching, and building automation tools to enhance system reliability. 🗂️ Requirements: Commercial experience with AWS, Azure, or GCP, Strong proficiency in Python, Strong proficiency in Java, Hands-on experience designing and maintaining CI/CD pipelines, Experience with Jenkins, GitHub Actions, GitLab CI, or Azure DevOps, Practical knowledge of container ecosystems, Experience in incident management and production monitoring, Experience executing system deployments and infrastructure patching 📃 Skills: AWS, Azure, GCP, Python, Java, Jenkins, GitHubActions, GitLabCI, AzureDevOps, CI/CD, Containers, Monitoring, Automation, DevOps 🏢 Description: We are looking for a highly skilled Senior DevOps Engineer to take ownership of production stability and drive the aggressive automation of support operations. In this role, you will bridge the gap between infrastructure and application support, ensuring the reliability of multi-cloud environments while eliminating manual operational toil. Essential functions Production Operations & Support: Act as the first line of defense for system reliability. Monitor system health, manage incidents, and troubleshoot complex production issues. Support Automation: Write robust code and scripts to automate routine support activities, system patching, and deployment processes. CI/CD Management: Build, maintain, and optimize deployment pipelines across various tools (Jenkins, GitHub Actions, GitLab CI, Azure DevOps). Deployments & Patching: Execute seamless software deployments and infrastructure patching with minimal downtime. Qualifications Cloud Platforms: Commercial experience managing infrastructure in AWS, Azure, or GCP . Programming Skills: Strong proficiency in both Python and Java (essential for building automation tools and supporting the core application stack). CI/CD Mastery: Solid hands-on experience designing and maintaining pipelines (Jenkins, GitHub Actions, GitLab CI, or Azure DevOps). Containerization: Practical working knowledge of container ecosystems. Ops & Reliability: Deep understanding of incident management, production monitoring, and executing system deployments. 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 (NASDAQ: 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 enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: This role focuses on optimizing and validating large-scale machine learning workloads within a High-Performance Computing and compiler infrastructure environment. The engineer will manage performance benchmarking pipelines, conduct root-cause analysis of regressions, and automate infrastructure for reliable performance testing. It is a high-impact position centered on performance engineering, automation, and system-level debugging for next-generation hardware. 🗂️ Requirements: Strong proficiency in Python, Hands-on experience with SQL, Deep knowledge of Linux/Unix environments, Experience with Bash scripting, Ability to debug complex system-level issues, Experience with performance benchmarking and analysis, Clear technical documentation skills 📃 Skills: Python, SQL, Linux, Unix, Bash, HPC, CI/CD, Bazel, CMake, JAX, PyTorch, TensorFlow, GPU 🏢 Description: We are looking for an experienced Software Engineer in Performance Infrastructure to join our team. This position is part of a high-impact project for a world-renowned global tech leader and AI innovator . You will be focused on optimizing large-scale machine learning workloads for next-generation hardware within a High-Performance Computing (HPC) and Compiler Infrastructure environment. Your core mission will be to manage the end-to-end health, precision, and reliability of performance benchmarking pipelines, working at the intersection of automated infrastructure and performance engineering. Responsibilities: Performance Analysis & Validation: Evaluate results from automated benchmarking suites to detect and analyze performance shifts and shifts in metrics. Root-Cause Analysis: Perform deep-dive root-cause analysis on bisection results to identify specific code changes responsible for performance regressions. Infrastructure Automation: Develop and maintain Python-based tooling for benchmark automation, hardware configuration management, and automated data recovery. System Debugging: Troubleshoot failures within the benchmarking pipeline, including script errors, environment misconfigurations, and resource allocation issues in distributed clusters. Data Pipelines & Dashboards: Maintain and enhance data pipelines and visualization tools to ensure high-fidelity performance metrics are consistently available for engineering teams. Technical Documentation: Develop and maintain engineering playbooks and best practices to improve consistency in performance testing and incident investigation. Min requirements: Strong proficiency in Python for systems automation, data processing, and integration. Hands-on experience with SQL for querying large datasets and managing performance metrics. Deep knowledge of Linux/Unix environments, shell scripting (Bash), and command-line development. Exceptional analytical and problem-solving skills with the ability to debug complex system-level issues. Clear written communication skills for documenting technical investigations and collaborating across globally distributed teams. Would be a plus: Practical experience with distributed build and test systems (e.g., Bazel / CMake ). Strong familiarity with CI/CD pipelines and automated regression testing. Basic understanding of hardware accelerators ( GPUs ) or machine learning frameworks (e.g., JAX, PyTorch, TensorFlow ). Background in Performance Engineering or SRE (Site Reliability Engineering). 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 (NASDAQ: 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 enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Senior Full-Stack Engineer role focused on building and maintaining internal applications that connect in-house experts with millions of clients on a large-scale consumer platform. The position involves leading complex projects, shaping features from concept to deployment, and driving technical decisions using modern practices like TDD and continuous delivery. The role combines hands-on development with technical leadership and cross-functional collaboration. 🗂️ Requirements: 5+ years of professional software development experience, Experience as Technical Lead, Extensive hands-on experience with Ruby on Rails, Extensive hands-on experience with TypeScript, Experience with Next.js, Experience with React, Experience with CSS/Sass, Experience with GraphQL, Experience with Apollo, Experience designing and consuming APIs, Ability to lead complex technical projects, Experience with TDD, Experience with continuous delivery, Experience with service-oriented architecture 📃 Skills: Ruby, Rails, TypeScript, Next.js, React, CSS, Sass, GraphQL, Apollo, TDD, CI/CD, SOA, API 🏢 Description: We are looking for a Senior Full-Stack Engineer to join project for a leading US-based tech-driven consumer platform. In this role, you will build and maintain the internal applications that empower thousands of in-house experts to connect with millions of clients. By combining human expertise with best-in-class AI and recommendation algorithms, your work will have a direct, high-visibility impact on client retention and operational efficiency. You will be joining a collaborative, agile-inspired team of bright and kind engineers who value integrity, innovation, and trust, while utilizing modern practices like TDD, continuous delivery, and service-oriented architecture. Responsibilities: Lead the execution of complex projects within your team and across multiple engineering units. Act as an engaged, hands-on team member - lead meetings, create technical design documents, and pair program with other engineers. Collaborate closely with product, design, UX, data science, and mobile partners to shape features from concept to deployment. Provide technical leadership through mentorship, timely feedback, and code reviews, actively investing in the career growth of your teammates (team size: 1 Lead + 3 Senior FTEs). Break down large projects into actionable milestones and deliver sustainable results against measurable goals. Use data to frame business problems and drive technical decisions, guiding other engineers toward solutions that balance quality with pragmatism. Proactively communicate status updates, scope changes, and timeline shifts to teammates, stakeholders, and leadership. Participate in on-call rotations and help improve the on-call experience for others. Min requirements: 5+ years of professional software development experience. Have an experience as a technical lead Extensive, hands-on experience with Ruby on Rails, TypeScript, Next.js, React, and CSS/Sass . Proven experience with GraphQL and Apollo , including both consuming APIs and designing schemas. Exceptional communication skills with a track record of setting clear priorities and sharing them openly. A collaborative mindset - you enjoy mentoring other engineers, creating space for them to grow, and believe strong teams are built on trust and honesty. Would be a plus: Previous experience working in client-side / customer-facing teams. 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 (NASDAQ: 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 enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Fullstack (Kotlin + React) role focused on delivering a production-grade internal operations application critical to a cloud platform cutover, while supporting infrastructure observability. The position combines complex frontend state management and RBAC with JVM backend development and GCP-based cloud deployments. It requires strong autonomy in navigating legacy systems and ensuring high-quality, regulated releases. 🗂️ Requirements: 3–5 years professional software engineering experience, Minimum 2 years building complex frontend applications in production, Proficiency in React and TypeScript, Experience with complex state management (Redux or Context API), Implementation of frontend RBAC and user rights management, At least 1 year experience with Kotlin or other JVM language, Ability to read and modify Java codebases, 1–2 years hands-on experience with GCP, Experience with GKE, Cloud Run, and Terraform, Strong SQL skills with complex queries, Experience with Apache Airflow workflows, Experience with unit and integration testing with high code coverage, Ability to work within strict PR and peer review processes, Fluent written English 📃 Skills: Kotlin, Java, React, TypeScript, Redux, ContextAPI, GCP, GKE, Kubernetes, CloudRun, Terraform, SQL, Airflow, Python, RBAC, Spring, Ktor, Bigtable, Kafka, C++ 🏢 Description: We are looking for a Fullstack developer (Kotlin+React) to join a regulated, high-stakes global tech ecosystem and drive the delivery of critical enterprise infrastructure. Your core mission will be split between supporting a vital infrastructure observability workstream and taking ownership of a new, business-critical internal operations application. This system serves as a zero-buffer, hard go-live dependency for cutting over a massive, multi-year platform to the cloud. If you are a highly autonomous engineer who thrives on complex state management, robust backend integrations, and production-grade cloud deployments, we want to hear from you. Responsibilities: End-to-End Application Ownership: Design, build, and deliver a production-grade operational administration interface, enabling operators to manage complex lifecycle data components. Access Control & Security: Implement frontend Role-Based Access Control (RBAC) with complex user rights management, ensuring tailored role-based rendering and access control per user type (admin, operator, read-only). Backend Integration & Feature Development: Write, modify, and extend clean backend code in Kotlin and Java to build robust data validation pipelines and integrate with core data services. Cloud Infrastructure & Deployment: Provision, deploy, and manage containerized applications within Google Cloud Platform (GCP) utilizing Kubernetes (GKE), Cloud Run, and Terraform. Observability & Scripting: Develop, integrate, and maintain Python monitoring and alerting scripts to create robust dashboards, manage technical metrics, and support test tooling frameworks. Quality Assurance & Testing: Implement rigorous unit and integration testing workflows with exceptionally high code coverage to meet strict, formal quality sign-off standards. Codebase Navigation & Autonomy: Rapidly onboard into a large, complex legacy platform, independently resolving technical blockers and owning your deliverables with minimal supervision. Min requirements: Experience: 3 to 5 years of professional software engineering experience, including a minimum of 2 years building complex frontend applications in production (business tools, internal platforms, or financial applications preferred). Frontend Expertise: Solid Mid-to-Senior level proficiency in React and TypeScript, with a proven track record of handling complex state management (Redux or Context API) and implementing frontend RBAC. JVM Backend Skills: Practical experience (at least 1 year) with Kotlin or another JVM language, alongside the ability to read, debug, and modify existing Java codebases. GCP Production Experience: 1 to 2 years of hands-on experience with Google Cloud Platform, specifically utilizing GKE (Kubernetes), Cloud Run, and infrastructure provisioning via Terraform. Data & Workflow Automation: Strong SQL skills with the ability to query complex data models, coupled with practical experience orchestrating workflows via Apache Airflow. Crucial Non-Technical Skills: Extreme technical autonomy, rapid onboarding skills into unfamiliar codebases, and fluent written English for async communication and peer reviews. Process Alignment: Comfort working within a highly regulated corporate framework where every deliverable undergoes strict pull request workflows and formal peer sign-off. Would be a plus: Domain Knowledge: A strong background in financial services, fintech, investment banking, or handling complex reference data layers. Advanced JVM Ecosystem: Deep understanding of modern Spring or Ktor architectural patterns. Data Storage Frameworks: Understanding of Google Cloud Bigtable architectures and how massive data layers are stored and read. Low-Level Code Awareness: Ability to read and understand existing C++ code within a legacy system context. Advanced Streaming: Familiarity with real-time data streaming architectures using tools like Apache Kafka or distributed risk batches. 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 (NASDAQ: 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 enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Senior Java Developer role focused on designing, implementing, and maintaining high-volume, low-latency, mission-critical systems across the full development lifecycle. The position includes architectural decision-making, performance optimization, code quality ownership, and technical mentorship within a hybrid work model in Poland. 🗂️ Requirements: Proven experience as Senior Java Developer in enterprise applications, Deep expertise in Java, Strong experience with Spring Boot and Hibernate, Master-level knowledge of relational databases, Strong knowledge of OOP, design patterns, algorithms, data structures, Experience designing and implementing REST or RPC APIs, Advanced unit testing skills, Experience with TDD, Experience with Git, Experience with CI/CD pipelines 📃 Skills: Java, Spring, SpringBoot, Hibernate, PostgreSQL, MySQL, SQL, OOP, REST, RPC, JUnit, Mockito, TDD, Git, CI/CD, AWS, GCP, Azure, Kafka 🏢 Description: We are looking for an experienced Senior Java Developer to design, implement, and maintain high-volume, low-latency applications for mission-critical systems. In this role, you will take ownership of the full development lifecycle - from writing efficient, testable code to driving architectural decisions. You will also act as a technical guide for the team, mentoring junior developers and fostering a culture of engineering excellence. Work Model: Hybrid in Warsaw / Wroclaw / Krakow / Gdansk Responsibilities: Design, implement, and maintain high-volume, low-latency Java applications for mission-critical systems across the full development lifecycle. Write high-quality, efficient, and testable code for critical components, ensuring strong functionality and performance. Analyze and solve complex technical problems, including system failures, performance bottlenecks, and scalability challenges through root-cause analysis. Provide technical leadership and mentorship to the engineering team, conducting rigorous code reviews and fostering a culture of software excellence. Refactor and continuously improve the existing codebase to enhance maintainability and extensibility while actively addressing technical debt. Ensure the overall quality and reliability of software products by driving a strong testing culture (unit, integration, and end-to-end tests). Create and maintain technical documentation, including architecture diagrams and best-practice guides, to facilitate onboarding and knowledge sharing. Minimum requirements: Experience: Proven track record as a Senior Java Developer building enterprise-grade applications. Core Tech: Deep expertise in Java and its ecosystem, particularly Spring Boot and Hibernate . Database Mastery: Master-level knowledge of relational databases ( PostgreSQL, MySQL , etc.). Architecture & Design: Strong grasp of Object-Oriented Programming (OOP), design patterns, algorithms, data structures, and APIs ( REST, RPC ). Testing: Master-level skills in unit testing ( JUnit, Mockito ) and a strong foundation in Test-Driven Development (TDD). Infrastructure: Solid competence in working with Git and CI/CD pipelines. Would be a plus: Experience with Cloud technologies (AWS, GCP, or Azure). Hands-on experience with Apache Kafka or other event-streaming 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 (NASDAQ: 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 enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Site Reliability Engineer role focused on leading the cloud platform layer of a large-scale enterprise migration to GCP, with full ownership of observability and FinOps capabilities. The position involves architecting cost attribution, distributed tracing, monitoring, and performance engineering solutions in a production-grade Kubernetes environment. You will work on complex distributed systems, extending multi-language codebases and managing infrastructure as code in a regulated enterprise setting. 🗂️ Requirements: 4–6 years software or DevOps engineering experience, 2–3 years hands-on cloud infrastructure management in production, Strong GCP expertise including GKE and Cloud Run, Proven experience building observability solutions with OpenTelemetry, Experience with distributed tracing and profiling in distributed systems, Advanced Python scripting for automation and tooling, Strong Terraform proficiency with multi-environment setups, Ability to read and modify Kotlin and Java codebases, Experience implementing monitoring, alerting, and SLOs for containerized/serverless services, Experience with infrastructure cost attribution and cloud billing APIs 📃 Skills: GCP, GKE, CloudRun, Kubernetes, OpenTelemetry, Terraform, Python, Kotlin, Java, FinOps, PubSub, Bigtable, Docker, SLO, Tracing 🏢 Description: We are looking for a Site Reliability Engineer to join a high-stakes global tech ecosystem and drive the delivery of a critical enterprise platform migration to the cloud. Your core mission will be to architect, build, and productionalize the observability and cost intelligence (FinOps) layer for a massive, multi-year financial platform transformation. You will take end-to-end ownership of the cloud platform layer, giving internal stakeholders full visibility into platform behavior, performance, and infrastructure spend. Working alongside a nearshore team of senior engineers, you will solve highly complex architectural challenges in a production-grade, distributed system. Responsibilities: End-to-End Infrastructure & FinOps Ownership: Architect and implement a cloud usage and cost attribution dashboard, providing detailed per-pod and per-service cost breakdown using cloud billing APIs and internal FinOps hubs. Advanced Observability & Tracing: Instrument end-to-end distributed tracing using OpenTelemetry, configuring collectors within Kubernetes environments and exporting traces to cloud monitoring systems utilizing RED metrics. Performance Engineering & Stress Testing: Write custom tooling from scratch to deliver database performance monitoring, load testing, and trend analysis for critical underlying storage layers. Monitoring & Alerting Automation: Build and deploy scalable production monitoring, custom alerting policies, and SLO tracking for containerized and serverless services. Infrastructure as Code: Independently manage, write, and apply infrastructure modifications using Terraform, working within established enterprise repository standards, modules, and environment state management. Cross-Language Codebase Extension: Read, debug, and extend existing platform code across a diverse stack including Kotlin, Java, and Python to seamlessly integrate technical metrics without disrupting business logic. Quality & Release Assurance: Implement rigorous unit testing with high code coverage for all newly developed monitoring tools to comply with strict enterprise quality gates and sign-offs. Min requirements: Experience: 4 to 6 years of professional software or DevOps engineering experience, with at least 2 to 3 years of hands-on cloud infrastructure management in production. Advanced Cloud Infrastructure: Deep operational proficiency with Google Cloud Platform (GCP), specifically with managing and configuring workload-level alerting on Google Kubernetes Engine (GKE) and Cloud Run. Observability & OpenTelemetry: Proven track record of building observability solutions in distributed systems, using OpenTelemetry (both auto and manual instrumentation) alongside distributed tracing and profiling tools. Strong Automation Scripting: Intermediate-to-advanced fluency in Python for writing custom test tooling, metrics integration scripts, and backend automation from scratch. Solid Infrastructure as Code: Strong proficiency in Terraform, including experience with multi-environment setups, workspaces, and corporate module standards. Polyglot & JVM Familiarity: Practical ability to read, understand, and modify existing backend codebases written in Kotlin and Java. Crucial Non-Technical Skills: Extreme technical autonomy to resolve blockers independently, rapid onboarding skills into large unfamiliar codebases, and fluent written English for async alignment and pull requests. Process Alignment: Ability to thrive in a highly regulated enterprise environment with strict peer reviews, robust documentation requirements, and formal deployment procedures. Would be a plus: Domain Knowledge: Previous experience working within financial services, fintech, investment banking, or other highly regulated industries. Enterprise Streaming Tools: Working knowledge of cloud messaging systems (such as Cloud Pub/Sub) utilized for inter-service communication. Advanced Storage Engines: Familiarity with high-throughput distributed database architectures, such as Google Cloud Bigtable. Systems Languages Awareness: Ability to read or debug foundational code written in low-level systems languages like Rust or C++ during multi-stack production deployments. 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 (NASDAQ: 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 enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.