{"id":3471817,"url":"https://alion.io/job/xebia-senior-data-streaming-engineer","title":"Senior Data Streaming Engineer","company":{"id":1386,"name":"Xebia","domain":"xebia.com","url":"https://alion.io/company/xebia","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Recruitee","truth_index":{"grade":"C","score":64,"open_postings":33,"ghost_share":0.606,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":56,"computed_at":"2026-10-31T05:58:55Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Bulgaria"],"countries":["BG"],"hiring_countries":["BG"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":34000,"max_usd":89000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2679},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"Databricks","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"Kubernetes","optional":false},{"name":"Snowflake","optional":false}],"status":"live","first_seen_at":"2026-10-29T16:09:21Z","employer_posted_date":null,"last_verified_at":"2026-10-29T16:09:21Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions.\n\nWe specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.\n\nIn the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing.\n\nWe are looking for a Senior Data Streaming Engineer to join a project delivered for our international client, working with large-scale, event-driven systems and real-time data processing.\n\nYou will join a dedicated Streaming team responsible for building and operating production systems based on Kafka-compatible event streaming and Apache Flink. The role combines stream-processing development with the practical challenges of operating distributed systems, ensuring reliable event delivery, and managing stateful workloads in a cloud-native environment.\n\nYou will work hands-on across the streaming stack, contributing to production workloads running on AWS and Kubernetes, while developing services and components in Go.\n\nYou will be:\n\nbuilding and maintaining production-grade, Kafka-compatible event-streaming solutions,\n\nmanaging partitions, consumer groups, delivery guarantees, and schema evolution,\n\ndeveloping and maintaining stream-processing applications using Apache Flink,\n\nworking with event time, watermarks, state management, and checkpoints,\n\ndeveloping services and components in Go,\n\ndeploying and operating streaming workloads on AWS-based infrastructure,\n\nrunning and troubleshooting workloads on Kubernetes,\n\ncontributing to the reliability, scalability, and operational stability of distributed streaming systems,\n\ninvestigating production issues and improving the performance and resilience of streaming applications,\n\ncollaborating with other engineers to evolve the streaming platform and follow engineering best practices.\n\nYour profile:\n\nhands-on production experience with Kafka-compatible event-streaming technologies,\n\npractical understanding of Kafka concepts, including partitions, consumer groups, delivery guarantees, and schema evolution,\n\nexperience developing stream-processing solutions with Apache Flink,\n\nunderstanding of Flink concepts, including event time, watermarks, state management, and checkpoints,\n\npractical experience developing services or components in Go,\n\nexperience working with AWS infrastructure,\n\nhands-on Kubernetes experience, including deploying, operating, and troubleshooting workloads,\n\nstrong problem-solving skills and the ability to work with distributed systems in production environments.\n\nPractical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery.\n\nWork from the European Union region and a work permit are required.\n\nNice to have:\n\nexperience working with Kubernetes operators and Custom Resource Definitions (CRDs),\n\nexperience operating stateful or distributed workloads on Kubernetes,\n\nexperience troubleshooting performance, reliability, and scaling challenges in real-time data-processing systems.\n\nExperience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work.\n\nInterest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches.\n\nRecruitment Process:\n\nCV review – HR call – Interview – Client Interview – 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