Site Reliability Engineer

🏢 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 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: Senior Site Reliability Engineer role focused on ensuring reliability, performance, and resilience of enterprise products by bridging infrastructure and software engineering. The position involves hands-on Java/Spring Boot code fixes, Kubernetes-based container operations, incident response, and proactive architecture improvements. The engineer drives automation, observability, and security best practices across the SDLC. 🗂️ Requirements: 5+ years experience in SRE or Platform Engineering, Strong proficiency in Java, Strong proficiency in Spring Boot, Experience with Hibernate, Experience with Jenkins, Ability to read, analyze and fix application code, Hands-on experience with Docker, Hands-on experience with Kubernetes, Deep knowledge of Linux systems, Strong understanding of networking, Experience with distributed systems, Experience with monitoring and observability tools, Bachelor’s degree in Computer Science, Systems Engineering or equivalent experience 📃 Skills: Java, Spring, Hibernate, Jenkins, Docker, Kubernetes, Linux, Networking, Prometheus, Grafana, Splunk 🏢 Description: We are looking for an experienced Senior Site Reliability Engineer to join our team and oversee the reliability, resilience, and performance of our core enterprise products. In this role, you will bridge the gap between infrastructure operations and software engineering. You won't just react to alerts - you will proactively analyze system architecture, build automation, and dive deep into the application code (Java/Spring Boot) to fix bugs and eliminate issues at their root. Responsibilities: Architecture & Reliability: Understand the end-to-end product topology from both infrastructure and application perspectives. Identify bottlenecks, scale limitations, and unstable components, driving long-term resolutions before they impact production. Incident Response & RCA: Respond to outages, provide L3 on-call technical support (on rotation), and perform blameless Root Cause Analysis (RCA) to implement permanent fixes. Hands-on Engineering: Address defects, perform code bug fixes directly in production, and recommend architectural improvements during incident analysis. Security & Vulnerability Management: Oversee vulnerability management for applications and containers, manage patching processes, ensure compliance, and monitor certificate expirations and renewals according to global best practices. SRE Advocacy & SDLC: Represent the SRE organization in design reviews, capacity planning, and operational readiness exercises. Partner closely with development teams to embed reliability best practices early in the SDLC. Automation & Mentoring: Build automation tools to reduce manual toil and improve efficiency. Spread SRE culture, create standard documentation, and provide technical mentorship to junior team members. System Health: Oversee the production environment by tracking availability, applying learnings from observability tools, and becoming a Subject Matter Expert (SME) on core issuing products. Min requirements: Experience: 5+ years of experience in Site Reliability Engineering (SRE) or Platform Engineering roles. Software Engineering: Strong proficiency in Java, Spring Boot, Hibernate , and Jenkins. Ability to read, analyze, and fix application code. Containerization: Hands-on expertise with Docker and container orchestration using Kubernetes . Infrastructure: Deep knowledge of Linux systems, networking, and distributed architectures. Observability: Strong understanding of monitoring, logging, and observability tools (e.g., Prometheus, Grafana, Splunk). Education: Bachelor’s degree in Computer Science, Systems Engineering, or equivalent practical experience. Soft Skills: Excellent problem-solving abilities and strong communication skills. Would be a plus: Infrastructure as Code & Cloud: Hands-on experience with tools like Terraform or Ansible, alongside familiarity with major public cloud providers (AWS, GCP, or Azure). Advanced Networking & Service Mesh: Knowledge of service mesh technologies (e.g., Istio, Linkerd) for traffic management, security, and observability in microservices architectures. Industry Experience: Previous background in the FinTech, payments, or banking sectors, with an understanding of high-security compliance standards (e.g., PCI-DSS). 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: Hands-on Site Reliability Engineer role focused on ensuring stability, scalability, and observability of a mission-critical distributed risk and analytics platform in hybrid cloud environments. The position centers on production reliability, incident response, automation, and continuous improvement of monitoring and deployment processes. You will collaborate with engineering teams to strengthen system resilience, performance, and operational standards. 🗂️ Requirements: Strong Java experience in distributed systems, Experience with observability and monitoring tools, Hands-on experience with hybrid cloud environments (preferably GCP), Experience with CI/CD pipelines and automation tools, Solid knowledge of Linux systems administration, Understanding of RDBMS fundamentals, Experience with job schedulers (e.g., Control-M), Ability to lead incident response and root-cause analysis 📃 Skills: Java, Grafana, Prometheus, Loki, OpenTelemetry, GCP, Jenkins, Ansible, Linux, SQL, Control-M, CI/CD 🏢 Description: We’re looking for a seasoned Site Reliability Engineer to support a high‑performance, mission‑critical risk and analytics platform used across global trading and finance environments. You’ll play a key role in ensuring the stability, scalability, and observability of complex distributed systems running across hybrid cloud infrastructure. In this role, you’ll take ownership of production reliability driving incident response, conducting root‑cause analysis, improving monitoring capabilities, and delivering automation that reduces operational toil. You’ll work closely with development teams, platform engineers, and service management leads to strengthen resilience, refine processes, and enhance the engineering culture around availability and performance. This is a hands on technical position suited to someone who thrives in high‑throughput environments, communicates clearly, and enjoys solving deep engineering problems in real time. Core Responsibilities Maintain and improve the reliability, uptime, and performance of distributed applications. Lead incident response, triage complex issues, coordinate recoveries, and deliver structured post‑incident reviews. Enhance observability—designing and evolving monitoring, alerting, logging, and tracing frameworks. Drive continuous improvement across automation, deployment processes, and service stability. Collaborate with cross‑functional teams to influence architecture, design, and operational standards. Support CI/CD pipelines, environment configuration, and vulnerability remediation. Contribute to a knowledge‑driven culture through documentation, tooling, and best‑practice adoption. Required Skills & Experience Strong Java background with proven experience supporting or developing distributed systems. Observability tooling expertise (Grafana, Prometheus, Loki, OpenTelemetry or similar). Hands‑on with hybrid cloud environments , ideally with GCP or another major cloud provider. CI/CD and automation experience (e.g., Jenkins, Ansible). Solid understanding of Linux , RDBMS fundamentals , and job schedulers (e.g., Control‑M or equivalents). Strong analytical mindset with a methodical approach to troubleshooting. Excellent communication skills and comfort working in Agile teams.

🏢 Summary: Senior Big Data Developer role focused on full ownership of a modern AWS-based data platform, including architecture, infrastructure, and performance optimization. The position involves building end-to-end data pipelines, managing cloud infrastructure as code, and implementing a scalable data lakehouse using advanced big data frameworks. The role emphasizes deep AWS expertise, Spark-based processing, and workflow orchestration in a high-performance environment. 🗂️ Requirements: Expert-level Core Python proficiency, Strong experience with PySpark and Apache Spark, Extensive hands-on experience across AWS services (S3, Lambda, EMR, Redshift, Glue, VPC, ECS, ECR, SQS), Strong proficiency in AWS CDK and AWS CLI, Experience designing and managing Airflow workflows, Experience with Apache Iceberg table format, Advanced SQL skills, Experience with REST API integration, Proficiency in Bash scripting, Experience with infrastructure-as-code and cloud security (IAM, KMS, Secrets Manager) 📃 Skills: Python, PySpark, Spark, AWS, S3, Lambda, EMR, Redshift, Glue, VPC, ECS, ECR, SQS, CDK, CLI, Airflow, StepFunctions, Iceberg, SQL, REST, Bash, IAM, KMS, Athena, RDS, Pydantic, Alembic 🏢 Description: We are looking for a Senior Big Data Developer to join our team and take full ownership of a modern, high-performance data platform. Essential functions End-to-End Data Engineering: Design and build complex ingestion and transformation pipelines using Python (PySpark) and Apache Spark. Cloud Infrastructure Ownership: Take full responsibility for our AWS environment, utilizing AWS CDK to manage everything from VPCs and Load Balancers to EMR clusters and ECS containers. Orchestration & Workflow: Develop and manage sophisticated data workflows using Airflow (MWAA) and AWS Step Functions. Modern Data Lakehouse: Implement and optimize storage layers using Apache Iceberg and Redshift, adhering to Medallion Architecture and advanced design patterns. Infrastructure-as-Code: Architect self-healing and scalable infrastructure through AWS CDK, ensuring security and compliance via IAM, KMS, and Secret Manager. Performance Tuning: Monitor and optimize query performance across Athena, Glue, and RDS to ensure low-latency data access. Qualifications Python Mastery: Expert-level proficiency in Core Python, including experience with Pydantic and Alembic. Deep AWS Expertise: Extensive hands-on experience across the AWS ecosystem (S3, Lambda, EMR, Redshift, Glue, VPC, ECS, ECR, SQS). IaC & Automation: Strong proficiency in AWS CDK and the AWS CLI; ability to manage your own cloud infrastructure independently. Big Data Frameworks: Proven experience with Apache Spark (PySpark) and modern table formats like Apache Iceberg. Data Orchestration: Hands-on experience with Airflow for managing complex data lifecycles. SQL & APIs: Advanced SQL skills and a solid understanding of REST API integration. Scripting: Proficiency in Bash for system-level automation. Would be a plus Backend Engineering Background: Prior experience in software engineering (beyond just data) is a major plus, specifically building scalable microservices. Familiarity with distributed design patterns and data governance. 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: 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 Java Engineer role focused on maintaining and optimizing the core (non-UI) Android application codebase, ensuring stability and performance of critical system components. The position involves deep log analysis, advanced debugging, and delivering high-impact fixes directly to production. You will also design observability mechanisms and lead technical investigations in collaboration with cross-functional teams. 🗂️ Requirements: Strong professional experience in Java, Experience reading and writing complex Java code, JVM runtime management, Writing robust automated tests, Advanced debugging of large-scale systems, Ability to analyze and interpret complex logs, Strong SQL skills for querying and aggregating log data, Upper-Intermediate (B2+) English level, Availability to work onsite in Krakow at least 3 days per week 📃 Skills: Java, JVM, SQL, Android, Kotlin, HAL, SIP, TLS, DNS, OSI 🏢 Description: We are looking for a highly skilled Senior Java Engineer to join our elite engineering group. In this role, you will work at the very heart of the world’s most widely used mobile operating system, maintaining and optimizing its core codebase. Responsibilities: Core Systems Maintenance: Maintain and optimize the Android application core codebase (non-UI), ensuring the stability of vital system components. Deep-Dive Analysis: Perform high-level analytical work, reading logs from various sources and using specialized tools to trace complex code behavior. Bug Resolution & Debugging: Identify, reproduce, and resolve critical bugs within the Java/Kotlin codebase, delivering high-impact fixes directly to production. Instrumentation & Observability: Design and implement advanced logging and tracing mechanisms to gain precise insights into system performance and reliability. Discovery & Research: Act as a technical lead in the discovery phase for new support requests, investigating requirements and technical constraints. Strategic Collaboration: Work closely with cross-functional teams and the world's leading OS engineers to align technical solutions with global standards. Min requirements: Experience: strong professional experience in Java development (reading/writing complex code, managing JVM runtime, and writing robust tests). Analytical Mastery: Exceptional analytical skills with a proven ability to debug large-scale systems and interpret complex log data. Data Proficiency: Strong experience with SQL to design queries for extracting and aggregating relevant data from system logs. Communication: Excellent communication skills with the ability to act as a technical consultant for global partners. Language: Spoken and written English at an Upper-Intermediate (B2+) level or above. Office Presence: Readiness to work from our innovation hub in Krakow at least 3 days a week . Would be a plus: Android Internals: Hands-on experience with Android (Frameworks, HAL, or low-level app debugging). Networking Protocols: Understanding of the OSI model and experience with telecommunications protocols (SIP, TLS, DNS). Modern Tooling: Familiarity with Kotlin and Google-specific internal development frameworks. Leadership Potential: Experience or strong desire to mentor junior engineers and take ownership of the release cycle. 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.