{"id":2632054,"url":"https://alion.io/job/sun-tech-innovation-middle-python-be-engineer","title":"Middle Python BE Engineer","company":{"id":4422776,"name":"Sun Tech Innovation","domain":"suntechinnovation.com","url":"https://alion.io/company/suntechinnovation","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BambooHR","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Dubai, United Arab Emirates"],"countries":["AE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Feature Store","optional":false},{"name":"Python","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"Databricks","optional":true},{"name":"Grafana","optional":true},{"name":"Kubernetes","optional":true},{"name":"LLM","optional":true},{"name":"Neo4j","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Prometheus","optional":true},{"name":"pySpark","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-01T00:00:00Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-26T13:34:25Z","board_verified":true,"closed_at":null,"days_open":25,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":25},"description":"About us\nWe are a product R&D company that creates solutions for the dynamic iGaming ecosystem. Our\nmission is to build cutting-edge platforms that reinvent the iGaming industry.\nAbout the team\nWe are a focused engineering team of 5 to 9 people at a multi-product tech SaaS company. We\nwork across personalization, recommendation, fraud detection, and some GenAI, through real-\ntime, near-real-time, and batch pipelines. The team is a blend of Python backend engineers, ML\nengineers, QA (manual and automation), a data engineer, and data scientists. Our shared\nmandate is to take experimentation from our data scientists and turn it into robust, production-\ngrade systems, either as standalone services or integrated into wider platforms.\nThe role\nYou will build and operate production backend systems alongside senior engineers and a hands-\non engineering manager, owning your work end to end and growing into the harder problems.\nThe systems you work on are either part of a larger SaaS backend or run as standalone services:\nbatch and event-driven pipelines, stream consumers, feature stores, REST APIs, scheduled jobs\nand background workers.\nResponsibilities\nDesign and build production Python services: APIs, stream consumers, pipelines, feature\nstores, scheduled jobs, background workers\nWrite and tune the SQL and schemas these services depend on\nUphold engineering standards: code quality, testing, observability, deployment discipline\nProductionize data scientists' experimentation into reliable services\nDiagnose and fix problems in production\nContribute to design discussions and the implementation approach for the systems you\nwork on\nReview code and help raise the bar for what the team ships\nTake part in the team's on-call rotation for the systems you build and operate\nRequirements\n3+ years of backend engineering experience\nStrong Python: async, data processing, and working with Redis, Kafka and database clients\nDeep database skills - non-trivial SQL, query plans, index design, transactions and isolation\nlevels, and concurrency\nExperience across relational and non-relational stores, and when to choose which\nGood working knowledge of Docker and CI/CD, enough to partner well with DevOps\nExperience owning a service in production\nNice to have\nGraph databases (Neo4j or similar)\nPostgreSQL internals: MVCC, autovacuum and bloat, partitioning, connection pooling\nPySpark, Databricks\nKubernetes\nExperience building LLM-powered systems, including the vector stores behind them\nFraud detection, recsys, or personalization systems experience\nPrometheus and Grafana\nSaaS or high-scale product domain experience\nWhy join us\nWork on high-scale, high-throughput backend systems\nBroad range of technologies, stacks, and problems\nTake experimentation from data scientists and turn it into production systems\nA strong engineering culture that values technical depth and ownership\nA technically strong environment with a modern stack and a mature Agile culture\nHigh autonomy, decision-making authority, and close cooperation with leadership\nRoom to contribute your own ideas for improvement and see them implemented\nFlexibility through hybrid and remote working\nA distributed team across Dubai and Europe\nDiscretionary annual bonus, based on individual, team, and company performance\nComprehensive medical insurance\nAnnual flight allowance\nVisa sponsorship\nAnnual leave\nLearning and conference budget\nCompany-paid AI coding assistant\nInterview stages\n1. HR interview (30 minutes) - initial conversation about your experience, career goals, and\ncultural fit\n2. Technical interview (1 hour) - in-depth technical interview covering relevant skills\n3. Technical design interview (1.5 hours) - system and database design\n4. Final interview (30 minutes) - a discussion with the hiring manager, focusing on role-\nspecific competencies and alignment with company values\n5. 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