Big Data Developer

🏢 Summary: Backend Developer role focused on modernizing and optimizing backend services, upgrading core technologies, and implementing automation using GenAI tooling. The position involves migrating authentication systems to OAuth, consolidating data stores, and building Spark-based batch pipelines. It emphasizes performance improvements, scalable architecture, and robust backend engineering practices. 🗂️ Requirements: Hands-on experience with production Java services, Hands-on experience with production Scala services, Familiarity with Play Framework internals, Experience with Spark for pipeline-heavy workloads, Experience with OAuth-based authentication patterns 📃 Skills: Java, Scala, Play, Spark, OAuth, JDK, GenAI 🏢 Description: Summary The Backend Developer role is aimed at enhancing and modernizing backend services and pipelines within the organization. This position primarily focuses on improving system performance, ensuring robust authentication mechanisms, and implementing automation to streamline processes. Main Responsibilities Modernise backend services and pipelines by upgrading to the latest JDK, Scala 3.x, and Play Framework 3.x. Apply GenAI tooling to automate code transformations, dependency resolution, and compatibility fixes, producing reusable tools and documentation. Migrate authentication frameworks from legacy APIs to OAuth-based solutions across various backend services. Replace multiple data stores with a single versioned table, creating Spark/Java batch pipelines for backfill/migration and extending Scala/Play backends. Key Requirements Hands-on experience with production Java/Scala services. Familiarity with Play Framework internals. Experience with Spark for pipeline-heavy work. Comfortable with OAuth-based authentication patterns. Nice to Have Familiarity with React/TypeScript. For DevOps-leaning candidates: experience with Gradle, scripting, and CI/CD pipelines. Other Details Location: Not specified. Team Structure: Not specified. Tools/Methodologies: Java, Scala, Play Framework, Spark, OAuth.

🏢 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 Big Data Engineer role focused on designing and optimizing large-scale data processing solutions using Spark and Scala within the financial sector. The position involves building resilient data pipelines, supporting production systems, and collaborating in Agile teams to deliver scalable data platforms. Hybrid work model based in Warsaw with up to two remote days per week. 🗂️ Requirements: 3-5 years experience in big data engineering, Strong expertise in Spark, Proficiency in Scala or Java, Knowledge of Python, Experience with DevOps practices, Experience with CI/CD tools, Understanding of microservices architecture, Fluent English, Legal right to work in the European Union 📃 Skills: Spark, Scala, Java, Python, DevOps, CI/CD, Microservices, Airflow, Git, Scrum, BigData 🏢 Description: Empower data-driven innovation — shape the future of financial technology! Warsaw-based opportunity with hybrid work model (up to 2 remote days per week). As a Senior Big Data Engineer (Spark/Scala) , you will be working for our client, a leader in structured finance within the global banking industry. You will contribute to building and optimizing a cutting-edge data platform that supports complex business processes and facilitates collaboration across multiple stakeholders in the finance sector. Join us to drive impactful data solutions that fuel digital transformation and open new avenues for growth. Your main responsibilities: Design and develop solutions for collecting, transforming, and processing large datasets efficiently. Analyze data from multiple sources and translate insights into technical specifications. Implement and industrialize reliable, scalable, and resilient data processing jobs using Spark and Scala. Conduct code reviews and collaborate with team members to ensure continuous improvement. Contribute to agile teams delivering value through Scrum cycles, supporting innovative project delivery. Stay up-to-date with evolving big data technologies and implement best practices. Support applications, troubleshoot production issues, and ensure high quality standards. Produce comprehensive technical documentation, test plans, and project artifacts. You're ideal for this role if you have: 3-5 years of professional experience in big data engineering, ideally within banking or finance. Strong expertise in Spark and Java or Scala, with additional knowledge of Python, DevOps, CI/CD tools, and microservices. Fluency in English (Polish and French are a plus). Analytical mindset with excellent problem-solving skills. Proactive attitude and strong teamwork skills across global teams. Effective communication skills and ability to work across different time zones. It is a strong plus if you have: Knowledge of Airflow, GIT, and modern data architecture strategies. Experience with Agile methodologies and delivering solutions in fast-paced environments. Language Required for the role: Fluent English (required) Eligibility for the role: Only candidates with an existing legal right to work in the European Union will be considered for this role. #MAKEYourCareerBETTER Interested? Apply now and include your CV (preferably in English) along with a statement confirming your consent to the processing and storage of your personal data.

🏢 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: Backend Developer role focused on designing and building scalable, cloud-based applications using Java and Spring Boot in a microservices architecture. The position involves developing and deploying distributed, event-driven services on Azure using modern containerization and API technologies. The offer emphasizes building reliable, high-quality backend systems with up-to-date cloud-native practices. 🗂️ Requirements: Strong Java development experience, Experience with Spring Boot, Experience with microservices architecture, Experience with cloud-native applications, Familiarity with Azure, Knowledge of Kafka or similar messaging systems, Understanding of GraphQL or REST APIs, Experience with Docker, Experience with Kubernetes 📃 Skills: Java, Spring, SpringBoot, Microservices, Azure, Kafka, GraphQL, REST, Docker, Kubernetes 🏢 Description: We are seeking a talented Backend Developer to join our team, contributing to the design and development of modern, cloud-based applications. The role focuses on building scalable and maintainable services using up-to-date technologies and best practices. Key Responsibilities: Develop and maintain backend services using Java and Spring Boot . Build and support microservices solutions for distributed systems. Work with cloud platforms such as Azure , including event-driven architectures. Implement and consume APIs using GraphQL or REST. Package and deploy applications using Docker and Kubernetes . Collaborate with team members to deliver reliable, high-quality software. Required Skills & Experience: Strong background in Java development with Spring Boot . Experience with microservices and cloud-native applications. Familiarity with Azure , Kafka , or similar messaging/event systems. Understanding of API design ( GraphQL /REST). Practical experience with containerization ( Docker , Kubernetes ). Nice to Have: Knowledge of CI/CD practices and automated deployments. Experience with monitoring, logging, or observability in distributed systems.

🏢 Summary: The offer is for a backend-focused engineer working on modernising Java/Scala services and data pipelines, upgrading core frameworks, and migrating authentication to OAuth. The role involves heavy work with Spark-based batch pipelines and Play Framework services, with opportunities to apply GenAI tooling for large-scale code transformations. DevOps experience with build systems and CI/CD is an advantage. 🗂️ Requirements: Hands-on experience with production Java services, Hands-on experience with production Scala services, Familiarity with Play Framework internals, Experience with Spark for data pipelines, Experience with OAuth-based authentication patterns, Ability to modernise and upgrade JDK, Scala, and Play Framework versions, Experience building batch data migration pipelines, Experience extending and maintaining backend services 📃 Skills: Java, Scala, Play, Spark, OAuth, React, TypeScript, Gradle, CI/CD, JDK, GenAI 🏢 Description: What we're looking for • Hands-on experience with production Java/Scala services • Familiarity with the Play Framework internals • Spark experience for pipeline-heavy work • Comfortable with OAuth-based authentication patterns • React/TypeScript familiarity is a plus • For DevOps-leaning candidates: experience with build systems (Gradle), scripting, and CI/CD pipelines Example of work tasks • Modernise backend services and pipelines: upgrade to latest JDK, Scala 3.x, and Play Framework 3.x • Apply GenAI tooling throughout to automate code transformations, dependency resolution, and compatibility fixes — producing reusable tools, prompts, and a documented runbook • Migrate authentication across a large number of backend services from a legacy API to an OAuth-based solution. • Replace per-unit data stores with a single versioned table: build Spark/ Java batch pipelines for backfill/migration and extend Scala/Play backends

🏢 Summary: Scala/Spark Developer role focused on building and optimizing scalable data processing applications and distributed systems using modern big data technologies. The position involves developing ETL/ELT pipelines, improving Spark performance, and collaborating on international AI and data engineering projects. The offer includes flexible working conditions, private healthcare, training opportunities, and a B2B salary range of 28,500–30,000 PLN + VAT. 🗂️ Requirements: Commercial experience with Scala in production environments, Knowledge of functional programming concepts in Scala, Experience with Scala type system, collections, sbt, and testing frameworks, Hands-on experience with Apache Spark, Experience with Spark SQL and DataFrame/Dataset API, Experience designing and maintaining ETL/ELT pipelines, Knowledge of Spark performance optimization techniques, Experience troubleshooting Spark applications using Spark UI, Experience with large-scale distributed data processing, Understanding of software engineering best practices and code quality 📃 Skills: Scala, Spark, SparkSQL, DataFrame, Dataset, ETL, ELT, sbt, ScalaTest, munit, SparkUI, Kafka, Airflow, AWS, EMR, S3, Glue, Azure, GCP, Dataproc, Databricks, Hadoop, Hive, DeltaLake, Parquet, Avro, SQL, Docker, Kubernetes, Git, CI/CD, Cats, ZIO, Akka, Pekko, Python, Java 🏢 Description: Scala/Spark Developer We are looking for a Scala/Spark Developer to join an AI-first software engineering company delivering innovative AI, data, cloud, and IoT solutions for clients across Europe and beyond. As part of the engineering team, you will design, develop, and optimize scalable data processing solutions, build high-performance distributed systems, and work with modern big data technologies on challenging international projects. Responsibilities Design, develop, and maintain scalable data processing applications using Scala and Apache Spark; Build, optimize, and maintain ETL/ELT pipelines processing large volumes of data; Develop efficient Spark applications using Spark SQL and the DataFrame/Dataset API; Optimize Spark jobs by improving partitioning strategies, shuffle operations, caching, and join performance; Troubleshoot and resolve performance issues using Spark UI and monitoring tools; Collaborate with data engineers, software developers, and stakeholders to design scalable data processing solutions; Participate in code reviews and contribute to software quality, performance, and engineering best practices. Requirements Strong commercial experience developing production applications in Scala, including functional programming concepts (immutability, pattern matching, higher-order functions), Scala type system, collections, sbt, and testing frameworks such as ScalaTest or munit, with the ability to write clean, maintainable, production-quality code; Proven hands-on experience with Apache Spark, including Spark SQL, DataFrame/Dataset API, designing and maintaining ETL/ELT pipelines, performance optimization (partitioning, shuffle optimization, broadcast joins, caching), and troubleshooting using Spark UI; Experience working in production environments with large-scale data processing and distributed data pipelines; Strong understanding of software engineering best practices, code quality, performance optimization, and maintainability. Nice to have Experience with Kafka and Spark Structured Streaming; Experience with Airflow or similar workflow orchestration tools; Experience with cloud platforms such as AWS (EMR, S3, Glue), Azure, GCP (Dataproc), or Databricks; Knowledge of the big data ecosystem, including Hadoop, Hive, Delta Lake, Parquet, and Avro; Experience with SQL, data modeling, data warehouses, and data lake architectures; Experience with Docker, Kubernetes, Git, and CI/CD pipelines; Familiarity with Scala libraries such as Cats, ZIO, Akka, or Pekko; Knowledge of Python or Java. We offer B2B salary: 28 500 -30 000 PLN + VAT; Flexible working conditions; Private healthcare, Multisport card, and professional training opportunities.

🏢 Summary: The role involves developing and maintaining scalable backend services for business-critical applications using Java within an agile environment. The position focuses on building RESTful APIs, implementing persistence layers, and ensuring system quality and stability. The developer collaborates on code reviews, debugging, and continuous improvement of backend solutions. 🗂️ Requirements: Strong experience with Java 17+, Hands-on experience with Spring, Hands-on experience with Spring Boot, Knowledge of Hibernate and ORM concepts, Experience with PostgreSQL, Experience with Git version control platforms, Strong debugging skills, Experience in agile development environments 📃 Skills: Java, Spring, SpringBoot, Hibernate, PostgreSQL, REST, Git, ORM 🏢 Description: Backend Developer (Java) We are looking for a Backend Developer to join a development team responsible for building and maintaining backend services for business-critical applications. The role focuses on developing scalable, maintainable solutions and contributing to the overall quality and stability of the system within an agile setup. Responsibilities: Develop and maintain backend services using Java 17+ Design and implement RESTful APIs with Spring and Spring Boot Work with relational databases, including schema design and query optimization in PostgreSQL Implement persistence layers using Hibernate Debug, troubleshoot, and resolve backend issues Collaborate with the team using a GitHub-like platform, including code reviews and version control Participate in agile ceremonies and contribute to continuous improvement Requirements: Strong experience with Java 17+ Hands-on experience with Spring and Spring Boot Knowledge of Hibernate and ORM concepts Experience working with PostgreSQL Familiarity with GitHub-like platforms and team workflows Strong debugging and problem-solving skills Experience working in agile development environments

🏢 Summary: The role focuses on developing and maintaining Java-based backend services that integrate multiple systems and support data processing workflows in a cloud environment. It involves building APIs, optimizing databases, and collaborating on ETL/ELT pipelines and CI/CD automation. The position requires close cooperation with data engineers to ensure reliable, high-quality data integration and system performance. 🗂️ Requirements: Strong experience in Java development, Good knowledge of SQL and relational databases, Experience with REST API development and system integrations, Understanding of ETL/ELT concepts and data pipelines, Experience with cloud environments, preferably Azure, Experience with CI/CD pipelines and DevOps practices, Ability to troubleshoot data flows and integration issues 📃 Skills: Java, SQL, REST, API, Azure, ETL, ELT, CICD, DevOps, AzureSQL, DataLake, Synapse, ADF, Messaging 🏢 Description: Key Responsibilities Design, develop, and maintain backend services and applications using Java . Build and support data integration layers and APIs connecting various systems. Collaborate closely with Azure Data Factory Engineers on ETL/ELT processes and data pipelines. Integrate systems using REST APIs and other data exchange mechanisms . Work with databases and optimize queries using SQL . Support data processing workflows and ensure data consistency and quality. Participate in CI/CD processes and contribute to automation and deployment pipelines. Troubleshoot and resolve issues related to data flow and system integrations. Collaborate with cross-functional teams including data engineers, analysts, and business stakeholders. Required Skills Strong experience in Java development . Good knowledge of SQL and relational databases . Experience working with REST APIs and system integrations . Understanding of data processing, ETL/ELT concepts , or data pipelines. Familiarity with cloud environments , preferably Microsoft Azure . Experience with CI/CD pipelines and DevOps practices . Strong problem-solving and analytical skills. Good communication skills and ability to work in a collaborative environment. Nice to Have Experience working with Azure Data Factory (ADF) or close collaboration with data teams. Familiarity with Azure services such as Azure SQL, Data Lake, or Synapse. Experience with messaging systems or event-driven architectures . Knowledge of data modeling concepts .