{"id":939996,"url":"https://alion.io/job/crypto-com-trading-analytics-developer-quantitative-trading-4","title":"Trading Analytics Developer, Quantitative Trading","company":{"id":2746,"name":"Crypto.com","domain":"crypto.com","url":"https://alion.io/company/crypto-com","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":75,"open_postings":17,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":43,"computed_at":"2026-11-03T05:54:40Z"}},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chicago, United States","New York, United States","Los Angeles, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":100000,"max":120000,"currency":"USD","period":"year","gross":null,"usd_annual":120000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A2A","optional":false},{"name":"AI Agents","optional":false},{"name":"Airflow","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"ClickHouse","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Flink","optional":false},{"name":"GitHub","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Grafana","optional":false},{"name":"Java","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangGraph","optional":false},{"name":"Linux","optional":false},{"name":"LLMOps","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"LangChain","optional":true},{"name":"Rest API","optional":true},{"name":"WebSockets","optional":true}],"status":"live","first_seen_at":"2026-09-15T06:08:49Z","employer_posted_date":"2026-09-15","last_verified_at":"2026-11-04T01:17:15Z","board_verified":true,"closed_at":null,"days_open":49,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":49},"description":"We are seeking an experienced Trading Analytics Developer to join our Quant Trading team and play a pivotal role in advancing our data and AI infrastructure. This role combines traditional quantitative development with cutting-edge AI platform engineering, focusing on building robust, scalable systems that serve both data analytics and artificial intelligence workloads. The ideal candidate will bridge the gap between high-performance trading systems and modern AI capabilities, ensuring reliability, performance, and actionable insights across both domains.\nJob Responsibilities\nData Platform & Analytics\nDesign, build, and operate high throughput batch and streaming data pipelines using Kafka, Flink, and ETL technologies\nDesign and build unified analytics engine designed for processing large-scale data using Apache Spark and related tools\nDevelop and optimize analytical data models for time-series, financial metrics, and trading activity\nImplement and manage analytical databases (ClickHouse, MongoDB, BigQuery, Snowflake, or similar) with cost-aware architecture\nBuild idempotent data pipelines with robust backfill and reconciliation capabilities\nCreate comprehensive monitoring for data quality, freshness, and pipeline reliability\nAI Platform Development\nDesign, build, and operate internal AI platforms serving multiple trading teams\nBuild reusable AI tooling including standardized RAG pipelines, prompt management, and self-service workflows\nCreate and maintain agent systems using modern frameworks (LangGraph, A2A, MCP) with focus on controllability and auditability\nJob Requirements\nMandatory Foundations\n5+ years production experience with both Python and Java in high-performance environments\nStrong software engineering fundamentals: system design, data structures, algorithms, data integrity, accuracy and performance optimization\nExpertise in Linux, Github, and modern CI/CD practices\nProven experience with AWS cloud services and Kubernetes orchestration\nComfort working with large-scale, complex datasets in financial/trading contexts\nData Platform Expertise\nAdvanced SQL with window functions and query optimization, realtime data synchronization together with database design and infrastructure support\nExperience with data workflow and messaging orchestration (Airflow, Jenkins, AMPS etc.)\nMetric design and implementation for trading analytics (PnL, risk, balance and trade reconciliation, backfill and performance tuning)\nTime-series data visualization with Grafana, TradingView, web-based interactive dashboards and BI tools etc.\nKafka, Flink, and event processing in production environments\nAI Platform Capabilities\nRetrieval system evaluation methodologies and quality frameworks\nRAG pipeline architecture and optimization techniques\nLLMOps practices including model lifecycle and prompt management\nExperience with AI agent frameworks in production settings like A2A and MCP\nPreferred Qualifications\nFinancial/Trading Domain\nExperience in trading systems, quantitative finance, or financial technology\nUnderstanding of market data, data subscription using Rest API / Web Socket\nKnowledge of cryptocurrency markets, defi and related technologies\nProfessional Attributes\nExcellent problem-solving skills with ability to perform under pressure\nStrong communication skills for cross-team 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