Data-oriented SRE (Fintech)

🏢 Summary: Long-term remote contract for a Platform Engineer/SRE to design, automate, and scale Azure-based infrastructure with a strong focus on AKS and large-scale observability. The role involves building and maintaining cloud-native platforms, managing Prometheus/Thanos at scale, and implementing Infrastructure as Code and CI/CD automation. The engineer will ensure secure, reliable networking and support further platform growth. 🗂️ Requirements: Minimum 5 years experience as Platform Engineer or SRE, Hands-on production experience with Azure, Hands-on production experience with AKS, Experience with Terraform, Experience with CI/CD pipelines (GitHub Actions or Azure DevOps), Experience operating Prometheus and Thanos at scale, Knowledge of Grafana and observability ecosystems, Strong understanding of cloud networking, Understanding of security best practices, Python for automation 📃 Skills: Azure, AKS, Terraform, CI/CD, GitHub, AzureDevOps, Prometheus, Thanos, Grafana, Docker, Kubernetes, Python, Ansible, Puppet, Networking 🏢 Description: We are looking for: Platform Engineer / SRE General info: Location:100% remote Start: ASAP Duration: long term General info: contract, full-time Rate: 190 - 230 PLN/h Responsibilities: Design and automate platform infrastructure in the Azure environment, primarily based on AKS. Configure and scale workloads, including APIs, databases, and processing components. Build and maintain integrations and architectural patterns connecting dozens of system components. Manage hundreds of Prometheus/Thanos instances and prepare the platform for further large-scale growth. Implement and maintain Infrastructure as Code using Terraform, CI/CD pipelines, Docker/Kubernetes, and Python-based automation. Design and manage networking at the architectural level, ensuring secure and reliable communication between platform components. Requirements: Minimum 5 years of experience in a Platform Engineer or Site Reliability Engineer (SRE) role. Hands-on experience with Azure and AKS in production environments. Good knowledge of Grafana and the broader observability ecosystem. Experience with Terraform and CI/CD pipelines (GitHub Actions and/or Azure DevOps). Experience operating Prometheus and Thanos at scale. Solid understanding of cloud networking fundamentals and security best practices. Python skills for automation; experience with Ansible or Puppet is a plus.

🏢 Summary: Senior Data Platform Engineer role focused on designing, building, and operating scalable, highly available data persistence systems for distributed services. The position combines backend engineering, platform reliability, and cloud-native data infrastructure to improve performance, scalability, and observability of global data ecosystems. Hybrid work model with competitive salary and comprehensive benefits. 🗂️ Requirements: 5+ years of software engineering experience in production systems, Strong backend engineering skills (Python, Java, or Kotlin), Experience with large-scale, data-intensive systems, Solid understanding of distributed systems fundamentals, Experience in cloud environments (AWS preferred), Experience with relational or NoSQL databases, Hands-on experience with large-scale data pipelines, Experience with event-driven or streaming architectures, Understanding of end-to-end data flow (ingestion, transformation, storage, access), Experience designing scalable and reliable data systems 📃 Skills: Python, Java, Kotlin, Kafka, Spark, PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch, AWS, Terraform, ETL 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Senior Data Platform Engineer to join the Datastores team. This team is responsible for building and operating the core data persistence layer used by application services across the organization. In this role, you will design and improve the systems that store, access, and scale critical data across distributed services. It is a hands-on engineering position where you will work at the intersection of backend engineering, platform reliability, and cloud-native data infrastructure. Your work will directly influence the scalability, performance, and reliability of the company’s global data ecosystem. Key takeaways: Stack: Python, Kafka, Spark, PostgreSQL, AWS Salary: 23.000 - 30 000 PLN gross per month on Employment Contract Working model: hybrid - 3x weekly from the office Location: ul. Grzybowska 60, Warsaw Recruitment process: A call with Motife recruiter (30 min) Coding Interview (1h) Interview panel: architecture & system design discussion; Hiring Manager meeting (up to 2h in total) Responsibilities: Data Infrastructure Engineering Design, build, and operate backend systems that rely on scalable and highly available data persistence layers. Contribute to architectural decisions around distributed data systems, multi-region persistence, and global scalability. Improve the reliability and performance of production datastores used by critical services. Data Performance & Optimization Partner with service teams to improve database schema design, query performance, and data modelling. Optimize data access patterns and indexing strategies for relational and NoSQL databases. Support teams in designing systems that scale efficiently under high load. Developer Experience & Platform Tooling Build and maintain self-service tooling that enables engineers to provision and manage databases and caching layers. Contribute to infrastructure automation using tools such as Terraform and internal developer platforms. Improve observability and operational insight into datastore performance and reliability. Platform Reliability & Observability Implement monitoring, metrics, and tracing strategies to improve visibility into production data systems. Develop autoscaling and performance optimization strategies for critical data infrastructure. Support operational excellence by reducing manual processes and improving system resilience. Requirements: Technical Expertise 5+ years of experience in software engineering, building and operating production systems Strong backend engineering fundamentals (e.g. Python, Java, or Kotlin) Experience working with large-scale, data-intensive systems Solid understanding of distributed systems fundamentals (e.g. scalability, latency, reliability, data consistency) Experience working in cloud environments (preferably AWS) Familiarity with relational or NoSQL databases (e.g. PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch) Data Systems & Architecture Hands-on experience with large-scale data pipelines and data processing systems Exposure to event-driven architectures, streaming or batch processing (e.g. Kafka, Spark, ETL workflows) Understanding of end-to-end data flow: ingestion (how data enters the system) transformation (how it is processed) storage & access (how other services consume it) Experience designing systems where data performance, scalability, and reliability are critical Collaboration & Engineering Mindset Ability to work cross-functionally with service teams to improve system design and data access patterns. Strong problem-solving skills with a focus on performance, scalability, and reliability. Clear communication skills and a collaborative engineering approach. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If you’re excited about building developer platforms that scale, empower teams, and set new standards for engineering excellence, we’d love to hear from you. Apply via our careers page and please submit your CV in English .

🏢 Summary: Senior Data Platform Engineer role focused on designing, building, and operating scalable, highly available data persistence systems for distributed services. The position combines backend engineering, cloud-native infrastructure, and data platform reliability to improve performance and scalability of global data systems. It is a hands-on role working with large-scale data pipelines, streaming, and cloud environments. 🗂️ Requirements: 5+ years of software engineering experience in production systems, Strong backend programming skills in Python, Java, or Kotlin, Experience with large-scale, data-intensive systems, Solid understanding of distributed systems fundamentals, Experience with cloud environments, preferably AWS, Experience with relational or NoSQL databases, Hands-on experience with large-scale data pipelines, Experience with event-driven architectures or streaming systems, Understanding of end-to-end data flow and data modeling, Experience designing scalable and reliable data systems, Experience with infrastructure automation tools 📃 Skills: Python, Java, Kotlin, Kafka, Spark, PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch, AWS, Terraform, ETL 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Senior Data Platform Engineer to join the Datastores team. This team is responsible for building and operating the core data persistence layer used by application services across the organization. In this role, you will design and improve the systems that store, access, and scale critical data across distributed services. It is a hands-on engineering position where you will work at the intersection of backend engineering, platform reliability, and cloud-native data infrastructure. Your work will directly influence the scalability, performance, and reliability of the company’s global data ecosystem. Key takeaways: Stack: Python, Kafka, Spark, PostgreSQL, AWS Salary: 23.000 - 30 000 PLN gross per month on Employment Contract Working model: hybrid - 3x weekly from the office Location: ul. Grzybowska 60, Warsaw Recruitment process: A call with Motife recruiter (30 min) Coding Interview (1h) Interview panel: architecture & system design discussion; Hiring Manager meeting (up to 2h in total) Responsibilities: Data Infrastructure Engineering Design, build, and operate backend systems that rely on scalable and highly available data persistence layers. Contribute to architectural decisions around distributed data systems, multi-region persistence, and global scalability. Improve the reliability and performance of production datastores used by critical services. Data Performance & Optimization Partner with service teams to improve database schema design, query performance, and data modelling. Optimize data access patterns and indexing strategies for relational and NoSQL databases. Support teams in designing systems that scale efficiently under high load. Developer Experience & Platform Tooling Build and maintain self-service tooling that enables engineers to provision and manage databases and caching layers. Contribute to infrastructure automation using tools such as Terraform and internal developer platforms. Improve observability and operational insight into datastore performance and reliability. Platform Reliability & Observability Implement monitoring, metrics, and tracing strategies to improve visibility into production data systems. Develop autoscaling and performance optimization strategies for critical data infrastructure. Support operational excellence by reducing manual processes and improving system resilience. Requirements: Technical Expertise 5+ years of experience in software engineering, building and operating production systems Strong backend engineering fundamentals (e.g. Python, Java, or Kotlin) Experience working with large-scale, data-intensive systems Solid understanding of distributed systems fundamentals (e.g. scalability, latency, reliability, data consistency) Experience working in cloud environments (preferably AWS) Familiarity with relational or NoSQL databases (e.g. PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch) Data Systems & Architecture Hands-on experience with large-scale data pipelines and data processing systems Exposure to event-driven architectures, streaming or batch processing (e.g. Kafka, Spark, ETL workflows) Understanding of end-to-end data flow: ingestion (how data enters the system) transformation (how it is processed) storage & access (how other services consume it) Experience designing systems where data performance, scalability, and reliability are critical Collaboration & Engineering Mindset Ability to work cross-functionally with service teams to improve system design and data access patterns. Strong problem-solving skills with a focus on performance, scalability, and reliability. Clear communication skills and a collaborative engineering approach. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If you’re excited about building developer platforms that scale, empower teams, and set new standards for engineering excellence, we’d love to hear from you. Apply via our careers page and please submit your CV in English .

🏢 Summary: Senior Data Platform Engineer role focused on designing, building, and operating scalable, highly available data persistence systems for distributed services. The position combines backend engineering, cloud-native infrastructure, and data platform reliability to support global, data-intensive applications. The engineer will enhance performance, scalability, and observability of production datastores across a multi-region environment. 🗂️ Requirements: 5+ years of software engineering experience in production systems, Strong backend programming skills (Python, Java, or Kotlin), Experience with large-scale, data-intensive systems, Solid understanding of distributed systems fundamentals, Experience with cloud environments, preferably AWS, Hands-on experience with relational or NoSQL databases, Experience with large-scale data pipelines and data processing systems, Experience with event-driven architectures or streaming/batch processing, Understanding of end-to-end data flow (ingestion, transformation, storage, access), Experience designing scalable, high-performance, reliable data systems 📃 Skills: Python, Java, Kotlin, Kafka, Spark, PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch, AWS, Terraform, ETL 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Senior Data Platform Engineer to join the Datastores team. This team is responsible for building and operating the core data persistence layer used by application services across the organization. In this role, you will design and improve the systems that store, access, and scale critical data across distributed services. It is a hands-on engineering position where you will work at the intersection of backend engineering, platform reliability, and cloud-native data infrastructure. Your work will directly influence the scalability, performance, and reliability of the company’s global data ecosystem. Key takeaways: Stack: Python, Kafka, Spark, PostgreSQL, AWS Salary: 23.000 - 30 000 PLN gross per month on Employment Contract Working model: hybrid - 3x weekly from the office Location: ul. Grzybowska 60, Warsaw Recruitment process: A call with Motife recruiter (30 min) Coding Interview (1h) Interview panel: architecture & system design discussion; Hiring Manager meeting (up to 2h in total) Responsibilities: Data Infrastructure Engineering Design, build, and operate backend systems that rely on scalable and highly available data persistence layers. Contribute to architectural decisions around distributed data systems, multi-region persistence, and global scalability. Improve the reliability and performance of production datastores used by critical services. Data Performance & Optimization Partner with service teams to improve database schema design, query performance, and data modelling. Optimize data access patterns and indexing strategies for relational and NoSQL databases. Support teams in designing systems that scale efficiently under high load. Developer Experience & Platform Tooling Build and maintain self-service tooling that enables engineers to provision and manage databases and caching layers. Contribute to infrastructure automation using tools such as Terraform and internal developer platforms. Improve observability and operational insight into datastore performance and reliability. Platform Reliability & Observability Implement monitoring, metrics, and tracing strategies to improve visibility into production data systems. Develop autoscaling and performance optimization strategies for critical data infrastructure. Support operational excellence by reducing manual processes and improving system resilience. Requirements: Technical Expertise 5+ years of experience in software engineering, building and operating production systems Strong backend engineering fundamentals (e.g. Python, Java, or Kotlin) Experience working with large-scale, data-intensive systems Solid understanding of distributed systems fundamentals (e.g. scalability, latency, reliability, data consistency) Experience working in cloud environments (preferably AWS) Familiarity with relational or NoSQL databases (e.g. PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch) Data Systems & Architecture Hands-on experience with large-scale data pipelines and data processing systems Exposure to event-driven architectures, streaming or batch processing (e.g. Kafka, Spark, ETL workflows) Understanding of end-to-end data flow: ingestion (how data enters the system) transformation (how it is processed) storage & access (how other services consume it) Experience designing systems where data performance, scalability, and reliability are critical Collaboration & Engineering Mindset Ability to work cross-functionally with service teams to improve system design and data access patterns. Strong problem-solving skills with a focus on performance, scalability, and reliability. Clear communication skills and a collaborative engineering approach. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If you’re excited about building developer platforms that scale, empower teams, and set new standards for engineering excellence, we’d love to hear from you. Apply via our careers page and please submit your CV in English .

🏢 Summary: Senior DevOps / SRE role focused on ensuring reliability, scalability, security, and performance of a cloud-native AWS platform. The position centers on infrastructure automation, CI/CD, Kubernetes operations, observability, and implementing SRE best practices to support highly available production systems. You will lead incident management, optimize cloud costs, and drive continuous improvement of platform resilience. 🗂️ Requirements: 5+ years in DevOps/SRE/Cloud/Platform Engineering, Strong Linux administration and troubleshooting, Production experience with Kubernetes, Experience with CI/CD tools, Expertise in Infrastructure as Code, Hands-on experience with AWS, Strong networking fundamentals, Experience with monitoring and logging tools, Scripting skills (Bash or Python) 📃 Skills: AWS, Kubernetes, Docker, Helm, Terraform, Ansible, CloudFormation, Linux, GitLab, Jenkins, GitHub, Azure, Prometheus, Grafana, ELK, Datadog, Splunk, Bash, Python, TCP/IP, DNS 🏢 Description: We are looking for a Senior DevOps / Site Reliability Engineer (SRE) to ensure the reliability, scalability, performance, and security of our platform and cloud infrastructure. You will play a key role in building and operating cloud-native systems, improving observability, automating operations, implementing SRE best practices (SLOs/SLIs), and supporting development teams to deliver highly available services. Key Responsibilities Design, implement, and maintain highly available and scalable infrastructure on AWS. Own and improve the reliability of production systems using SRE principles (SLO, SLI, error budgets). Build and manage CI/CD pipelines to support fast and safe software delivery. Develop and maintain Infrastructure as Code (IaC) using Terraform, Ansible, CloudFormation, etc. Manage and optimize container orchestration platforms (Kubernetes, Docker, Helm). Implement and maintain monitoring, logging, and alerting solutions (Prometheus, Grafana, ELK, Datadog, Splunk). Lead incident response, perform root cause analysis, and write postmortems to drive continuous improvement. Improve system performance, capacity planning, scaling strategies, and disaster recovery processes. Collaborate closely with development teams to improve deployment strategies and system resilience. Implement security best practices (IAM, secret management, vulnerability scanning, patching). Define operational standards, runbooks, documentation, and best practices for platform reliability. Participate in on-call rotation and provide senior-level support for critical production issues. Key Responsibilities (5 Main Missions) The DevOps / SRE lead will be responsible for the stability and evolution of the platform. Your role is structured around five main areas: Mission 1: AWS Infrastructure Management (Build & Run) Mission 2: CI/CD and Deployment Automation Mission 3: Monitoring, Observability, and Alerting: Global Monitoring , Log Management , Application Monitoring , Business Analytics Mission 4: Incident Management, Resilience, and Security Mission 5: FinOps and AWS Cost Optimization Key Requirements 5+ years of experience in DevOps / SRE / Cloud Infrastructure / Platform Engineering. Strong expertise in Linux systems administration and troubleshooting. Proven experience with Kubernetes in production environments. Strong experience with CI/CD tools (GitLab CI, Jenkins, GitHub Actions, Azure DevOps). Solid knowledge of Infrastructure as Code (Terraform highly preferred). Experience with AWS cloud platforms. Strong understanding of networking fundamentals (TCP/IP, DNS, load balancing, reverse proxies). Experience with observability tools: monitoring, metrics, logging, tracing. Strong scripting skills (Bash, Python, or similar). French advanced level. Nice to Have Experience with additional cloud platforms (Azure, GCP). Strong understanding of networking fundamentals.

🏢 Summary: Data Engineer role focused on building and scaling data infrastructure for advanced robotics systems. The position involves designing reliable batch and real-time pipelines, optimizing ETL/ELT processes, and implementing data governance across cloud platforms. You will collaborate cross-functionally to deliver high-quality, scalable data solutions supporting company-wide analytics and operations. 🗂️ Requirements: BS/MS/PhD in Computer Science, Mathematics, Computer Engineering or related field, or equivalent practical experience, 1–5 years of professional experience, Proficiency in Python and SQL, Hands-on experience with Rust, Go, Java, C#, or C++, Experience with Kafka, Spark, and lakehouse formats (Icebert, DeltaLake), Experience with AWS, GCP, or Azure, Strong debugging and problem-solving skills, Willingness to work extended hours and weekends if needed, Ability to work full time onsite in San Francisco 📃 Skills: Python, SQL, Rust, Go, Java, C#, C++, Kafka, Spark, Icebert, DeltaLake, AWS, GCP, Azure, Clickhouse, Flink, Databricks 🏢 Description: About the Role Help us advance our robotics moonshot by scaling our data engineering efforts. Drive design and development of data infrastructure across our products and internal tools. You will play a critical role in working with a cross-functional team to architect and build advanced robotic systems. Responsibilities - Design, build, and maintain scalable, reliable data pipelines that support both batch and real-time analytics. - Develop and optimize ETL/ELT processes to ingest, transform, and integrate data from multiple sources into data warehouses and lakehouse platforms. - Drive and apply best practices in data modeling, pipeline architecture, query optimization, data quality, and data engineering standards. - Collaborate closely with finance, bizops, and engineering teams to understand data needs and deliver solutions. - Provide data engineering support to ensure data accessibility and usability company-wide. - Implement and maintain data governance frameworks to support compliance with internal policies and external regulatory requirements. - Evaluate and adopt modern data engineering technologies, tools, and best practices to improve scalability, reliability, and operational efficiency. - Document data engineering processes, designs, and architectures. Qualifications - BS/MS/PhD in Computer Science, Mathematics, Computer Engineering, or a related field, or equivalent practical experience. - 1-5 years of professional experience. - Proficiency in writing production-grade code in Python and SQL. - Hands-on experience with one of the following languages: Rust, Go, Java, C#, C++. - Strong debugging skills and the ability to diagnose and resolve issues efficiently. - Experience with Kafka, Spark and common lakehouse formats like Icebert, DeltaLake. - Experience working with cloud platforms like AWS, GCP, Azure. Preferred Experience - Experience with Clickhouse, Apache Flink, Databricks. - Experience on financial reporting and understanding of accountability. Additional Requirements - Willing to work extended hours and weekends if needed. - This position is based full time in our San Francisco headquarters. Compensation The pay range for this position at the start of employment is expected to be between $140,000 - $200,000/year. The exact offer may vary depending on job-related knowledge, skills, and experience. In addition to cash compensation, this position will also receive generous equity. Benefits - Unlimited Flexible Time Off. - Health insurance (medical, dental, vision). - Paid parental leave. - Commuter benefits including fully paid parking spots. - Referral bonus. - 401k retirement plan. - Equity program.

🏢 Summary: Senior Full-Stack Software Engineer role focused on building large-scale, cloud-based data processing solutions on AWS with a strong emphasis on serverless architectures. The position involves developing and maintaining web applications, APIs, and microservices while optimizing and modernizing existing cloud infrastructure. The engineer will collaborate across international teams to deliver scalable scientific and data-driven solutions. 🗂️ Requirements: Minimum 5 years of enterprise software development experience, Expert knowledge of Java with Spring and Hibernate or JPA, Strong understanding of microservices architecture and patterns, Expert knowledge of JavaScript and TypeScript, Experience with Angular or React and HTML5, Experience building REST APIs, Knowledge of SQL, NoSQL and graph databases, Strong AWS knowledge including core services, Hands-on experience with Docker, Experience with Git and GitOps workflows, Ability to deploy code to production environments, Experience working with Scrum methodology, Fluent English 📃 Skills: Java, Spring, Hibernate, JPA, JavaScript, TypeScript, Angular, React, HTML5, Git, GitOps, REST, SQL, NoSQL, AWS, S3, IAM, EC2, ECR, ECS, Lambda, Serverless, Docker, RabbitMQ, OAuth2, Scrum, Oracle, MySQL, MongoDB, Spock, CI 🏢 Description: We are a provider of digital transformation and technology consulting services with a portfolio of solutions for both clients who do not yet have Salesforce and large organizations that work on Salesforce and use its extensive capabilities ☁. We also provide body and team leasing services in IT, providing specialists in various fields. Model : remote Employment type: full-time Background & Project: A team specializing in Data Engineering and bioinformatics systems development is seeking experienced and motivated Senior Full-Stack Software Engineer with hands-on AWS experience . This role involves developing large-scale cloud-based data processing solutions, primarily using AWS. We are looking for self-motivated and proactive engineer to contribute to the development of highly scalable computing solutions built on AWS services, with a strong focus on serverless architectures. The position involves leveraging AWS services and improving existing infrastructure to optimize, modernize, and future-proof current solutions. The engineering team operates across multiple time zones, including Pacific Time (PT), Eastern Time (ET), and Central European Time (CET). Virtual meetings and collaboration via Slack may take place during the core working hours of the San Francisco (PT) time zone. During the first six months of onboarding, increased collaboration and some overlap with the PT time zone will be expected. Responsibilities: Work together in a collaborative and practical manner to address scientific softwareengineering challenges. Engage with both local and offshore engineering teams to assist in software development endeavors Leverage existing GenAI and RAG solutions and services developed by other teams tointegrate data and existing capabilities into internal chatbots to enhance usability anddata discovery Rapid prototyping and iterations to foster innovation and enable the company to exploresolutions in a shorter time-frame. Design, build and maintain the web application providing visibility to our data management platform Collaboratively and pragmatically solve scientific software engineering challenges. Collaborate with local – Polish, the US and Canada engineering teams to support software development efforts. Contribute to the broader scientific community through open-source software development. Requirements: Minimum 5 years of work experience related to software development in enterprise projects/products and expert knowledge regarding one of the following backend technologies: JAVA (very good knowledge of frameworks like Spring, Hibernate / JPA, knowledge of other JVM based programming languages is a plus); Understanding of microservice architectures, principles and patterns Expert knowledge of Javascript and TypeScript programming ( Angular 5+ or React,with good knowledge of HTML5. Experience building reusable web components. Knowledge of git and standard GitOps workflow (MRs, protected branch), conventional commits, semantic versioning, pre-commit hooks, Experience building APIs, good understanding of REST principles Knowledge of database techniques like SQL, NoSQL and graph databases Fluent in the usage of cloud computing models (IaaS, PaaS, SaaS) and good knowledge of containers connected with this DevOps mindset and excellent knowledge of cloudplatforms like AWS. Ability to deploy yourself code to production Docker (must have) AWS cloud (including S3, IAM, EC2, ECR, ECS, AWS Lambda, Serverless) Experienced in product development with Scrum methodologies Experienced in designing software components based on limited and evolving requirements Attention to details, focus on user/developer experience Ability to coordinate work and direct collaboration with the customer Fluent in English General knowledge RabbitMQ (or other similar message broker) Good communication skills, team player, work under tight deadlines. Nice to have: Good understanding of HTTP protocol (status code, headers, etc…) Basic knowledge of OAuth 2.0 Building distributed systems Automated testing – unit, int, e2e, performance, regression Spock (Groove DSL) CI pipelines Oracle/MySQL/Mongo We offer: Remote work model B2B contract Benefits package, Daily support from team leaders, Dedicated certification budget, Integration trips/events.

🏢 Summary: Hands-on Site Reliability Engineer role focused on building and scaling reliability practices across cloud and on-prem environments. The position involves improving performance, scalability, and resilience of production systems through automation, observability, and Kubernetes-based infrastructure. You will drive SRE standards and collaborate with engineering teams to enhance system stability and fault tolerance. 🗂️ Requirements: 4+ years experience in SRE, DevOps or similar roles, Strong experience with distributed systems, Strong experience with Kubernetes, Experience with AWS cloud, Hands-on automation experience with Python, Bash or Go, Solid understanding of CI/CD practices, Experience with observability and monitoring tools, Experience managing production systems 📃 Skills: Kubernetes, AWS, Python, Bash, Go, Prometheus, Grafana, CI/CD, SRE, DevOps 🏢 Description: We’re looking for a Site Reliability Engineer (SRE) to help build and scale reliability practices across our engineering organization. This is a hands-on role where you’ll work across cloud and on-prem environments, improving the performance, scalability, and resilience of critical production systems. 🔧 What you’ll be doing: • Driving SRE best practices, standards, and ways of working • Building and scaling observability & monitoring solutions (e.g. Prometheus, Grafana) • Working with Kubernetes-based infrastructure to ensure reliability and efficiency • Automating deployments, incident response, and recovery processes • Collaborating closely with engineering teams to improve system stability and fault tolerance • Contributing to a strong reliability culture (SLOs, post-mortems, continuous improvement) ✅ What we’re looking for: • 4+ years of experience in SRE / DevOps / similar roles • Strong experience with distributed systems, Kubernetes, and cloud (AWS preferred) • Hands-on approach to automation (Python, Bash, or Go) • Solid understanding of CI/CD and modern software delivery • Proactive mindset and strong ownership of production systems Name and surname*

🏢 Summary: 100% remote B2B contract role for an Expert Data Engineer to build and maintain distributed Big Data pipelines supporting decision-making processes in an international banking environment. The position focuses on near real-time processing of large-scale structured and unstructured data using Spark, Scala, and Hadoop ecosystems. It requires strong experience in data engineering, automation, and continuous delivery on Big Data platforms. 🗂️ Requirements: Minimum 5 years of experience with Spark and Scala, Minimum 7 years of experience with Python, Minimum 5 years of experience with Linux, Experience with distributed data processing engines, Experience with Hadoop ecosystem (Hive, Oozie, MapReduce), Strong SQL skills, Experience in building data flows, Expert-level knowledge of Git and BitBucket, Experience with unit testing (JUnit 5, Mockito, Spark testing), Advanced English (min. B2) 📃 Skills: Scala, Python, Spark, Hadoop, Hive, Oozie, MapReduce, SQL, Linux, Git, BitBucket, JUnit, Mockito 🏢 Description: Workplace: 100% remote Notice period: 30 days Form of cooperation: B2B contract with ITFS Rate: 140 - 170 PLN/h + VAT Client: international bank Technology stack: Scala, Python, Spark Language: English (min. B2) The recruitment process: screening call with ITFS (~ 20 minues)  → technical interview with the client → decision As an Expert Data Engineer you will be building data systems to support decision making processes. You will focus on developing and maintaining data pipelines. This position will require advanced technical depth and experience, and communication skills. What you’ll be doing: Building a distributed and highly parallelized Big data processing pipeline which process massive amount of data (both structured and unstructured data) in near real-time Leveraging Spark and Scala to transform corporate data to enable data products to be built Continuous delivery on Hadoop and other Big Data Platforms Automating processes where possible and are repeatable and reliable Must have: Experience in Spark & Scala - minimum 5 years; Experience in Python - minimum 7 years Experience in Linux - minimum 5 years Experience with distributed data processing engines like Spark Experience with Hadoop and (Hive, Oozie, map reduce, etc) Strong/Advanced SQL skills Previous experience in creating data flows BitBucket and GIT expert Unit testing Experience (Junit 5, Mockito, Spark testing) Advanced English skills Must-have knowledge and experience: To succeed in this role, we believe that you: Are collaborative and achieve your expectations through communication and teamwork Are curious, responsive and can understand the needs of others to ensure delivery of the desired results Work qualitatively and strive to always do things better Have a high level of self-motivation Nice to have: Code versioning strategy & Branching strategy Familiar with Agile/Safe framework We offer: Transparent terms of cooperation with a company with a secure and stable market position and opportunities for growth. Access to benefits (co-financing for Enel-med and Multisport healthcare packages, and a basic accounting package – free for up to three invoices per month).

🏢 Summary: 6-month on-site contract for a Platform Software Engineer to build and operate a production-grade application platform for a global AI product. The role covers the full lifecycle from deployment to runtime, ensuring reliability, scalability, and performance of distributed systems. You will evolve infrastructure and core platform services into a modular, high-performing architecture. 🗂️ Requirements: 6+ years in software engineering or platform/infrastructure roles, Strong experience with distributed systems, Experience with platform engineering, SRE, or infrastructure operations, Experience with multitenant environments, Experience with container orchestration, Experience working with external vendors and managed services, Experience operating production systems with focus on uptime and scalability 📃 Skills: Kubernetes, AWS, GCP, Cloudflare, Go, Rust, React, TypeScript, ClickHouse, BigQuery, Firestore, Spanner, Terraform, CI/CD, DNS, SSL 🏢 Description: emagine is looking for a Platform Software Engineer to one of the most exciting AI companies in Stockholm. Start: ASAP Length: 6 months with possible extension Location: Stockholm on-site 5 days per week About the role You will play a key role in building and operating the platform that runs applications in production. This includes the full lifecycle from deployment to runtime, ensuring reliability, scalability, and performance across a global user base. The platform handles everything behind the scenes when an application is launched: infrastructure provisioning, authentication, storage, logging, usage metering, and domain management. As part of a growing team, you will help evolve this platform into a more modular, scalable, and high-performing architecture. Key responsibilities Own and improve the application hosting and deployment pipeline Build and operate the runtime that serves applications in production Manage and evolve core platform services such as storage, logging, and workflows Design and maintain infrastructure for custom domains, including DNS and SSL at scale Evaluate, onboard, and migrate third-party services as part of a move towards best-of-breed architecture Ensure operational excellence through monitoring, alerting, incident management, and capacity planning Collaborate with vendors and ensure high service quality and SLA adherence What we are looking for Strong experience building and operating distributed systems Around 6+ years of experience in software engineering or platform/infrastructure roles Background in platform engineering, SRE, or infrastructure operations Experience with multitenant environments, container orchestration (e.g. Kubernetes), or edge runtimes Experience working with external vendors and managed services Strong operational mindset with focus on uptime, performance, scalability, and cost efficiency Nice to have Experience building large-scale multitenant control planes Experience with modern edge platforms (e.g. Cloudflare ecosystem) Contributions to cloud infrastructure or CNCF-related technologies Experience with log analytics platforms such as ClickHouse Familiarity with managed database services Proven track record of cost optimization in infrastructure Tech stack (examples) Frontend: React, Typescript Backend: Go, Rust Cloud: AWS, GCP, Cloudflare Data: ClickHouse, BigQuery, Firestore, Spanner DevOps: Kubernetes, Terraform, CI/CD, observability tooling