Вакансии

Задачи: гарантировать отечественным и зарубежным участникам торгов и инвесторам открытую, без перебоев работу торговой площадки. Требования: опыт работы с технологиями CI/CD, ETL, Kafka, ClickHouse, S3, Kubernetes, Spark, Python. Условия: работа в крупнейшей в России по объему торгов и по количеству клиентов бирже — ПАО Московская Биржа.

Location: Intellias Meet your recruiter Bohdana Rubets bohdana.rubets@intellias.com https://www.linkedin.com... Vacancy details Data Engineering Data Engineer Senior Bulgaria, Croatia, Poland Remote APPLY NOW REFER A FRIEND Let’s breathe life into great tech ideas! With 3,000 people globally, Intellias is a company where benchmark technological solutions are born. Join in and take your part in digitalizing the world. What project we have for you Our client is building the standard path for governed data sharing across product services, analytics, and AI/ML. The Data Platform team owns the contracts, control mechanisms, publication paths, catalog metadata, lifecycle rules, lineage, permissions, and runtime building blocks that make reusable data safe and practical at scale. This is a role for someone who wants to shape a platform early, while working on concrete production problems from the start. Our client already has the production systems, Kafka backbone, PostgreSQL databases, analytical consumers, and AI/ML use cases that need a better data foundation. The challenge is to turn that reality into a standard path that engineers actually want to use. Our first milestone is focused: centrally managed publishing tables in service-owned PostgreSQL databases, captured through Debezium CDC into Kafka, and registered in DataHub with ownership, lifecycle, lineage, and impact-analysis metadata. Longer-term, the platform expands toward self-service data products, governed materialisations, durable shared state, and reusable data across the client’s operational and analytical systems. This is not a role where you only maintain an existing reporting pipeline. You will help design and build the platform path that other engineering teams use when they publish and consume shared data. What you will do Design and build platform services, tools, and workflows for contract-driven data publishing and consumption. Build the first production path for platform-managed PostgreSQL publishing tables, Debezium CDC, Kafka topics, and catalog registration. Create GitOps-style workflows where contracts, schemas, ownership, lifecycle, compatibility, policy metadata, and runtime desired state are reviewed, validated, and reconciled as code. Build tooling that gives product engineers fast feedback before they publish or change data products. Help define how client models data products, publishing contracts, schema evolution, field stability, deletion semantics, access policy, lineage, and cost attribution. Operate and improve the CDC runtime model, including Kubernetes workloads, source-specific isolation, offsets, schema history, heartbeats, signal channels, lag visibility, replay, resnapshotting, and recovery. Integrate platform metadata into DataHub so engineers can discover data products, understand ownership, trace lineage, and reason about the impact of changes. Work with product, infrastructure, data engineering, analytics, and AI/ML teams to make the standard path easier and safer than bespoke point-to-point integrations. What you need for this Strong experience building and operating production software systems, preferably in platform, infrastructure, backend, or data-intensive environments. Deep understanding of distributed systems trade-offs: reliability, idempotency, replay, eventual consistency, ownership boundaries, compatibility, and operational failure modes. Practical experience with PostgreSQL or other relational databases, including schema design, migrations, transactions, replication, or operational performance. Experience with Kafka, event streaming, CDC, Debezium, or adjacent data-movement technologies. Direct Debezium experience is valuable, but strong fundamentals matter more. Experience building software that other engineers use: CLIs, internal platforms, control planes, automation, CI validation, developer tooling, or self-service workflows. Familiarity with Kubernetes and cloud or infrastructure platforms, including runtime isolation, deployment, observability, and operational ownership. Ability to turn ambiguous architectural direction into practical increments, make trade-offs explicit, and deliver useful production systems without waiting for perfect certainty. Clear written and spoken communication in English. This role involves aligning multiple engineering teams around standards, contracts, and ownership boundaries. Nice to have: DataHub or other data catalog, lineage, or governance systems. Open table formats such as Apache Iceberg, object-store-backed data lakes, S3, BigQuery, ClickHouse, or analytical storage systems. GitHub Actions, policy-as-code, infrastructure-as-code, controllers, operators, or reconciliation-based systems. Data contracts, schema registries, Protobuf, Avro, JSON Schema, compatibility checking, field-level metadata, or contract testing. Experience supporting analytics, AI/ML, feature-store-style access patterns, or cross-domain product-service integrations. Experience with JVM languages and Python, TypeScript, Go, or Ruby. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Location: Sydney Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. As an Infrastructure Support Engineer (AWS), you will play a key role in designing, maintaining, and securing cloud infrastructure to support critical business operations. The team works closely with development teams, DevOps, and system administrators to ensure seamless cloud functionality. Your future role at QRT: Design and implement custom AWS architectures to enhance the quantitative research and modelling processes of the desk Troubleshooting and resolving complex technical issues related to AWS infrastructure. Collaborate with quantitative researchers, developers, and data scientists to understand their needs and translate them into scalable, flexible, and secure cloud solutions Design and implement custom AWS architectures to enhance the quantitative research and modelling processes of the desk Develop automation scripts using Terraform, CloudFormation, and other tools to improve cloud management and efficiency. Work on continuous monitoring and optimizing performance and cost-effectiveness of cloud infrastructure. Evaluate and recommend new technologies to improve the reliability, scalability, and security of the company's cloud infrastructure Your present skillset: Troubleshooting should be core to your skill set and will be extremely useful to have ability to dive into issues without much context and troubleshoot the way to resolution. 8+ years' experience as a Cloud Architect or Engineer with a strong focus on AWS technologies. In-depth knowledge of AWS services, including EKS, EC2, S3, Lambda, RDS, VPC, IAM, CloudWatch, and others Proficiency with scripting languages (e.g. Python, Bash) Hands-on experience with configuration management tools (e.g. Ansible, Terraform). Experience with containers and orchestration technologies (e.g. Docker, ECS, Kubernetes) Experience with monitoring and performance tuning in cloud environments. Familiarity with agile software development methodologies Experience debugging with software development tools. Experience with working and troubleshooting with Windows and Linux OS administration. The ability to duplicate specific software error or AWS configuration to define the cause. Excellent verbal and written communication skills, and the ability to interpret and answer complex technical questions, provide and ensure user follow-up and contribute to knowledge base content. Maintain patience and composure as you help end users through their issues. AWS certifications (Solutions Architect, DevOps Engineer, etc) are a plus QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Разрабатывать новые функциональные модули и дорабатывать существующие на Angular и NestJS. Развивать функциональность аналитики, уведомлений, модерации и работы с видео.

Задачи: — развитие и поддержка AI-агентов и мультиагентных систем для крупного заказчика. Требования: — опыт промышленной разработки на Python 3.11+ с применением ООП, принципов SOLID, async, типизации, Pydantic v2, проектирования структуры сервиса, умение читать, писать и изменять чужой код; — опыт работы с FastAPI и интеграциями по HTTP, включая контракты, таймауты, ретраи и обработку ошибок внешних сервисов; — опыт прикладной работы с LLM: промпт-инжиниринг, работа с контекстом, tool calling, structured output; — желательно наличие опыта работы с GigaChat; — опыт работы с агентными сценариями: ReAct, LangChain, LangGraph, управление состоянием диалога, чекпоинты, ветвление, вызов инструментов, HITL, память сессии; — опыт разработки AI-агентов, мультиагентных систем и RAG-систем, знание протокола A2A или межагентского взаимодействия по контракту; — опыт работы с Jenkins, OpenShift/DropApp, OpenSearch/Elasticsearch, S3; — опыт вывода проекта в промышленную эксплуатацию и ведения релизного цикла от прототипирования до продакшна; — опыт организации наблюдаемости с использованием Langfuse, Phoenix, отладка по логам и трейсам, сбор метрик; — опыт тестирования агентов: детерминированные проверки логики (мокирование LLM и внешних сервисов, снапшоты промптов, контракты схем) и оценка качества ответов агента (эталонные кейсы, LLM as Judge). Личные качества: — умение переводить постановку аналитика в поведение агента и самостоятельно закрывать пробелы в сценарии без возврата задачи с формулировкой «мало деталей»; — способность объяснять заказчику на встречах, что сделает система, где модель ненадёжна и какой объём работ реалистичен, без обещаний точности LLM на уровне обычного API; — умение договариваться с тестировщиком о приёмке сценариев с нестабильной моделью, включая эталонные кейсы, допустимые расхождения и критерии дефекта; — навык выстраивания границ сервисов с Java-разработчиками: контракты, ошибки, таймауты, при этом самостоятельное ведение своей части; — ответственность за доведение багов и фич до выкладки, информирование о статусе в релизе, сохранение договорённостей со стенда; — умение писать коротко и по делу: комментарии к задачам, шаги воспроизведения, описание изменений в промптах и логике; — интерес к LLM и агентам, слежение за трендами в AI, понимание принципов работы нейронных сетей и умение их объяснить.

Run AWS infrastructure as code, with AI in the loop. Manage AWS infrastructure through Terraform using our pull-request-based GitOps workflow, and resolve configuration drift across regions.

-разрабатывать и развивать интеграционные решения на микросервисной платформе с использованием Java 25, Spring Boot 4 и Kubernetes. -реализовывать интеграционные взаимодействия между сервисами и системами с использованием Kafka и других технологий обмена сообщениями.

Задачи: — Разработка и поддержка функционала мобильного приложения на React Native, веб-панелей на React с TypeScript и бэкенда на Go — Использование AI-агента в IDE (VS Code) для написания, рефакторинга и отладки кода — Интеграция фронтенда с REST API бэкенда — Участие в код-ревью, написание понятного и поддерживаемого кода — Деплой и мониторинг сервисов в облаке AWS — Документирование выполненной работы и поддержание истории изменений в актуальном состоянии Требования: — Базовые знания нескольких технологий из стека: React Native, Go, React, TypeScript — Знания AWS (EC2, ECS, S3, чтение логов) — Уверенное владение VS Code — Опыт работы с AI-агентами в IDE (Claude Code, Cursor, Copilot и др.) — Навыки постановки задач агенту, проверки и доработки результатов — Опыт работы с Git (commit, push, branch, pull request) — Английский язык на уровне чтения технической документации — Желание быстро обучаться и осваивать новые технологии Будет плюсом: — Знания PostgreSQL / SQL — Опыт работы с Docker, CI/CD (GitHub Actions) — Опыт работы с Terraform и инфраструктурой как код — Понимание REST API, WebSocket — Опыт публикации мобильных приложений в App Store / Google Play Условия: — Работа над современным проектом с AI-first процессом разработки — Сильная команда и менторство — Реальная зона ответственности с первого дня — Зарплата от 6 000 000 сум в месяц на испытательный срок с возможным ростом до 8 000 000 сум — Бонусы по результатам работы от 50 до 200 долларов после испытательного срока — Опционы после квалификационного периода от 100 до 200 долларов — Влияние на развитие быстрорастущей e-commerce платформы нового поколения — Культура, ценящая любознательность, ответственность и инициативу

Location: Argentina Workplace: Remote Webflow is the agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize high-performing web experiences that drive predictable growth and strengthen brand trust. Building at Webflow will need grit, because we move fast, without ever sacrificing craft or quality. We’re looking for a Senior Software Engineer, Optimize/Analyze to help develop and scale Webflow Optimize products. You’ll design high-performance systems that adapt user experiences in real time, working with large-scale data processing and distributed computing to lift conversion and personalization at scale. Our team is fast-moving, data-driven, and experienced in personalization, ML infrastructure, and large-scale analytics. The next chapter is ambitious. We’re serving some of the world’s largest enterprises and rethinking what an AI-native conversion platform can be. This is a cross-team technical role: you’ll work across a large, revenue-generating system, help decide what it needs to become, and partner directly with Engineering, Product, and Design to ship it. About the role: - Location: Remote-first (Argentina) - Permanent, full-time employee (this is not a contractor position) - Application Information: - Application deadline: applications accepted on an ongoing basis until position is closed and filled - This posting is for a new position. As a Senior Software Engineer on the Optimize team, you'll: - Architect, design, and build scalable multi-tenant backend services and APIs for our Optimize product, including our MCP server. - Build with MongoDB, Druid, Airflow, AWS (EC2, S3), Python, and TypeScript/Node.js. - Define clean service and API boundaries, and design and optimize the MongoDB data models and queries that power recommendations. - Improve scalability and reliability through distributed architecture, caching strategies, and event-driven systems tuned for low latency. - Lead projects from design through launch that move team and engineering org goals. - Write and review maintainable, tested, performant code, and raise the quality bar for the team. - Author, collaborate on, and evaluate design documents. - Use AI tools in your daily work, and help the team build reliable systems on top of non-deterministic, LLM-backed components. - Partner with product engineers, PMs, and designers to ship end to end. ABOUT YOU Requirements: - BA/BS degree or equivalent experience - Business-level fluency to read, write and speak in English You’ll thrive as a Senior Software Engineer if you: - 5+ years building and shipping production backend services, with a track record of performant, high-quality code. - Depth in distributed systems: concurrency, asynchronous and eventually consistent processing, queues or streaming, and designing for failure. - Strong Python and/or TypeScript/Node.js, plus data modeling experience in MongoDB or a comparable database. - Experience with real-time analytics, event-driven architectures, and REST APIs. - Hands-on experience with AWS, containers, CI/CD, and observability, and comfort owning infrastructure. - Strong production debugging skills across services and layers of the stack. - A habit of valuing testing, documentation, and reliability as much as shipping, and communicating trade-offs clearly. - Curiosity and a proactive embrace of AI tools to work faster and expand the team’s impact. It would be a bonus if you had even one of the following: - Experience with Apache Spark, Airflow, or TensorFlow. - Familiarity with Kafka or other event streaming platforms. - Prior experience working on large-scale personalization, experimentation, or recommendation systems. OUR CORE BEHAVIORS - Build lasting customer trust. We build trust by taking action that puts customer trust first. - Win together. We play to win, and we win as one team. Success at Webflow isn't a solo act. - Reinvent ourselves. We don't just improve what exists, we imagine what's possible. - Own it all the way. We move fast because the moment demands it, and we hold ourselves accountable to deliver outcomes — for each other, and for customers.   BENEFITS - Ownership in what you help build. Every permanent Webflower receives equity (RSUs) in our growing, privately held company. - Health coverage that actually covers you. Comprehensive medical, dental, and vision plans for full-time employees and their dependents, with Webflow covering most premiums. - Support for every stage of family life. 12 weeks of paid parental leave for all parents and 6+ weeks of additional paid leave for birthing parents. Plus inclusive care for family planning, menopause, and midlife transitions. - Time off that’s actually off. Flexible vacation, paid holidays, and a sabbatical program to help you recharge and come back inspired. - Wellness for the whole you. Access to mental health resources, therapy and coaching. - Invest in your future. A 401(k) with 100% employer match (up to $6,000/year) in the U.S., and support for retirement savings globally. - Stipends to support our distributed team. Localized support for cell, Wi-Fi, and WFH expenses to help you settle into your best remote life. - Bonus for building together. All full-time, permanent, non-commission employees are eligible for our annual WIN bonus program.   Temporary employees may be eligible for paid holiday and time off, statutory leaves of absence, and company-sponsored medical benefits depending on their Fixed Term Contract and their country/state of employment.   BE YOU, WITH US At Webflow, equality is a core tenet of our culture. We are an Equal Opportunity (EEO)/Veterans/Disabled Employer and are committed https://webflow.com/diversity-equity-inclusion to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences. Employment decisions are made on the basis of job-related criteria without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by applicable law. Pursuant to the San Francisco Fair Chance Ordinance, Webflow will consider for employment qualified applicants with arrest and conviction records.   STAY CONNECTED Not ready to apply, but want to be part of the Webflow community? Consider following our story on our Webflow Blog https://webflow.com/blog, LinkedIn https://www.linkedin.com/company/webflow-inc-/, X (Twitter) https://twitter.com/webflow, and/or Glassdoor https://www.glassdoor.com/Reviews/Webflow-Reviews-E890506.htm.   PLEASE NOTE: We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Upon interview scheduling, instructions for accommodation requests will be administered. To join Webflow, you'll need a valid right to work authorization depending on the country of employment. If you are extended an offer, that offer may be contingent upon your successful completion of a background check, which will be conducted in accordance with applicable laws. We may obtain one or more background screening reports about you, solely for employment purposes. Webflow uses AI tools to assist in screening and evaluating applications. AI does not make final hiring decisions. For details on how we process your personal information, see Webflow’s Applicant Privacy Notice https://webflow.com/legal/applicant-privacy-notice.

Workplace: Удаленно Объединённая компания Wildberries и Russ — это международная технологическая компания, образованная в результате слияния двух лидеров рынка — IT-компании Wildberries и оператора наружной рекламы Russ. Мы - команда платформы данных в направлении Trust & Safety. Наша миссия - обеспечить T&S доступом к достоверным, актуальным и структурированным данным, предоставив надежную технологическую платформу и инструменты для их эффективного использования. Мы строим платформу, которая объединяет в себе решения для: - Хранения больших данных; - Высокопроизводительных запросов (OLAP); - Потоковой и батч-обработки; - Визуализации и оркестрации данных. Мы ищем разностороннего инженера, который сможет не только проектировать и разрабатывать пайплайны данных, но и активно участвовать в развитии платформенных сервисов, которому интересно разбираться в новом, который не боится задач на стыке разработки и дата инжиниринга. Обязанности Проектировать и разрабатывать потоковые процессы, которые читают события из Databus/Kafka и считают онлайн‑признаки, записывая их в Redis и Cassandra. Проектировать и разрабатывать пакетные процессы, которые читают данные из S3/Iceberg через Trino, считают офлайн‑признаки и пишут результаты обратно в S3/Iceberg и/или ClickHouse. Следить за тем, чтобы один и тот же признак был согласован между обучением и продакшеном (одна логика расчёта, единый контракт). Настраивать расписания, пересчёты и бэки, чтобы признаки обновлялись вовремя и выдерживали SLA по свежести. Работать с качеством данных: добавлять проверки, мониторить аномалии, разбирать инциденты, когда “признак поехал”. Совместно с DS и аналитиками придумывать новые признаки и помогать перевести их из экспериментальных скриптов в стабильные пайплайны. Требования от 5 лет опыта в роли Data Engineer / Backend+Data; Уверенный опыт работы с Kafka‑подобными очередями (Databus/Kafka): продюсеры/консьюмеры, партиционирование, ключи, обработка ошибок; Практический опыт со streaming‑движком (желательно Flink; Spark Structured Streaming подойдёт, если есть реальный прод‑опыт); Опыт работы с Redis или Cassandra как онлайновым хранилищем данных/признаков; Опыт работы с S3‑подобным хранилищем и табличным форматом (Iceberg/Delta/Hudi) и доступа к ним через SQL‑движок (Trino/Presto/Spark SQL); Отличное знание SQL и опыт работы с ClickHouse; Python на уровне уверенной разработки data‑скриптов и сервисной логики; Опыт настройки и сопровождения пайплайнов в Airflow; Понимание задач ML‑пайплайнов: train/serve skew, пересчёты признаков, влияние задержек и потерь событий. Условия Обучение и развитие: языковые клубы, собственный корпоративный университет, программы развития управленческих навыков и многое другое; Благополучие сотрудников: корпоративный пакет ДМС со стоматологией, корпоративный спорт, консультации психолога и дополнительные возможности аккредитованной IT-компании; Множество сообществ: клуб спикеров, футбола, йоги, шахмат и т.д.; Забота о семьях: создаем условия, в которых легко сочетать карьеру и заботу о близких – от гибкого подхода до масштабных проектов для детей сотрудников; Скидки и партнерские программы: на обучение, страхование, покупки и многое другое; Комфортная рабочая среда: бесплатное питание в офисе, современные офисы рядом с метро, корпоративная техника и портал для сотрудников.

Location: Belgrade We are looking for a Data Security Architect to join our Technical Data Protection team. The Technical Data Protection team is responsible for building and continuously improving Plata’s company-wide data security framework. We focus on protecting sensitive information throughout its entire lifecycle by implementing secure data architectures, access controls, encryption, masking, tokenisation, data loss prevention, and monitoring solutions across the organization. As a Data Security Architect , you will define and develop the company's target data security architecture, establishing consistent protection standards across products, data warehouses, cloud platforms, internal systems, and integrations. You'll collaborate closely with Data Engineering, Product, Architecture, Infrastructure, Information Security, Legal, Privacy, and Compliance teams to design scalable security solutions, strengthen data protection practices, and ensure sensitive information remains secure across all environments. Challenges that await you: Designing the company-wide target architecture for protecting sensitive, confidential, personal, financial, and payment data. Defining security requirements and controls for the complete data lifecycle - collection, transmission, processing, storage, analytics, sharing, archiving, and deletion. Working closely with DWH, Data Engineering, and Analytics teams to embed security controls into data platforms, pipelines, models, and integrations. Identifying critical data assets, repositories, data flows, trust boundaries, and potential exposure points. Establishing and improving the company’s data classification, labelling, ownership, and handling model. Defining architectural requirements for encryption, key management, tokenisation, masking, anonymisation, pseudonymisation, and secrets protection. Designing access control principles for data platforms, including least privilege, segregation of duties, role-based access control, and periodic access reviews. Defining security requirements for databases, data lakes, data warehouses, object storage, backups, APIs, analytical tools, and data exchange mechanisms. Performing data security risk assessments and threat modelling for new systems, products, integrations, and major architectural changes. Developing reusable security patterns, reference architectures, standards, and technical requirements for teams working with data. Defining the target architecture and coverage requirements for DLP, data discovery, data access monitoring, and other data protection technologies. Supporting regulatory and contractual requirements related to personal, financial, payment, and other regulated data. Building a long-term data security roadmap based on identified risks, business priorities, and regulatory requirements. Supporting security reviews and providing architectural sign-off for solutions that process critical or sensitive data. Defining data security metrics and helping measure control coverage, effectiveness, and maturity across the company. Providing technical guidance to the Data Security Engineer and other teams implementing data protection controls. Our technology stack: Data Platforms & Storage Cloud data warehouses and data lakes. Relational and NoSQL databases. Object storage and backup platforms. ETL/ELT pipelines, analytical platforms, and data integration services. Snowflake, PostgreSQL, Amazon Aurora, Amazon S3, and related technologies. Cloud & Infrastructure AWS and cloud-native security services. Kubernetes and Docker. IAM, OIDC/SAML SSO, and RBAC. Key management, secrets management, and encryption technologies. Security & Monitoring Data Loss Prevention solutions. Data discovery and classification technologies. SIEM and security monitoring platforms. Data access and audit logs. Jira Service Management and GitLab. What makes you a great fit: 3+ years of experience in Information Security, including hands-on experience with data security architecture or cloud security architecture. Strong understanding of data security principles and the complete data lifecycle. Experience designing security controls for DWH, databases, data lakes, cloud storage, data pipelines, APIs, and analytical platforms. Good understanding of data classification, access control, encryption, key management, masking, tokenisation, anonymisation, and DLP. Experience conducting architecture reviews, risk assessments, and threat modelling. Understanding of privacy, financial sector, and data protection requirements. Ability to translate security and regulatory requirements into practical technical controls. Ability to work effectively with Data Engineering, DWH, Architecture, Infrastructure, Product, Legal, Privacy, and Compliance teams. Strong analytical thinking and the ability to work with complex data flows and distributed environments. Clear written and verbal communication skills. English B2+ for working with documentation and international teams. Your bonus skills: Experience in fintech, banking, payments, or another highly regulated industry. Experience with Snowflake, AWS, PostgreSQL, or other modern data platforms. Knowledge of PCI DSS and privacy regulations applicable to personal and financial data. Experience implementing enterprise data classification or data security governance programs. Understanding of data mesh, zero trust, and security-by-design principles. Experience with Data Security Posture Management or Cloud Data Security solutions. Relevant certifications in cloud, security architecture, privacy, or data protection. Our ways of working : Innovative Spirit : a commitment to creativity and groundbreaking solutions Honest Feedback: valuing open, transparent communication Supportive Team: a strong, collaborative community Celebrating Achievements: recognizing our wins together High-Tech Environment: a team full of smart and revolutionary people who date to challenge the status quo of incumbent finances Our benefits : Relocation support to one of our hubs — Georgia, Cyprus, Kazakstan — with assistance for the employee and their family Flexible work from one of our offices or remote Healthcare Coverage Education Budget: Language lessons, professional training and certifications Wellness Budget: Mental health and fitness activity reimbursements Vacation Policy: Annual leave and paid sick leave as per applicable policies

Проектировать масштабируемую, надёжную и производительную архитектуру единой платформы данных. Разрабатывать и сопровождать техническую дорожную карту платформы, синхронизированную с бизнес-целями и потребностями исследователей.

Location: Intellias Meet your recruiter Bohdana Rubets bohdana.rubets@intellias.com https://www.linkedin.com... Vacancy details Data Engineering Data Engineer Senior Bulgaria, Colombia, Croatia, Poland, Portugal, Spain, Ukraine, United States Remote APPLY NOW REFER A FRIEND Intellias is looking for a Senior Data Engineer to join a digital healthcare initiative focused on building a large-scale health data platform that helps millions of people discover healthcare providers, connect with their health information, and make better-informed care decisions. This is a hands-on, high-ownership engineering role for someone experienced in building and operating data-intensive systems at scale. You will own critical data ingestion and processing capabilities, improve data quality and reliability, and develop AI-powered solutions for complex real-world healthcare data challenges. We are looking for an engineer who combines strong Python and data engineering expertise with cloud-native development, production ownership, and an AI-first engineering mindset . What project we have for you The project is building a FHIR-based healthcare data platform that aggregates provider information from national registries, EHR systems, healthcare networks, and partner data feeds. The platform ingests fragmented and often inconsistent healthcare data, transforms it into standardized FHIR resources, resolves duplicate identities and relationships, and makes trusted provider information available through high-scale search and data services. The engineering challenge goes well beyond traditional ETL. Provider data comes from hundreds of heterogeneous sources and contains duplicates, outdated records, conflicting identities, incomplete relationships, and inconsistent schemas. The platform must determine how these sources relate and continuously improve the accuracy and confidence of the resulting data. The technology landscape includes Python, Apache Spark, Prefect, AWS, Kubernetes, MongoDB, OpenSearch, and FHIR , with AI increasingly used both as part of the engineering lifecycle and within data-processing solutions. What you will do Design, build, and operate scalable data ingestion pipelines that onboard healthcare provider data from EHR systems, national registries, healthcare networks, and partner feeds. Transform heterogeneous source data into standardized, trusted data models, including FHIR-native resources . Own data quality end-to-end , including validation rules, quality thresholds, confidence scoring, automated monitoring, and alerting. Design and implement solutions for entity resolution, deduplication, relationship inference, classification, enrichment, and data quality scoring . Build and evolve distributed data processing pipelines using Python, Spark, and modern orchestration technologies . Improve pipeline reliability, scalability, observability, and performance so that new data sources can be onboarded efficiently and safely. Establish and evolve data governance standards , including schemas, staging models, validation processes, and data refinement workflows. Design and operate data storage and search solutions supporting large-scale healthcare datasets. Build AI-powered data tooling that improves the accuracy, automation, and intelligence of data processing workflows. Use modern AI development tools as an integral part of the engineering workflow to accelerate implementation, testing, debugging, documentation, and data analysis. Own production operations for the solutions you build, including monitoring, troubleshooting, incident response, and root-cause analysis. Partner with Analytics and Data Science teams to develop data quality dashboards, metrics, and reporting. Collaborate with Product and Business stakeholders to prioritize data sources and improvements based on customer and business impact. Contribute to technical design reviews and help establish scalable engineering patterns across the broader data platform. What you need for this 5+ years of professional experience building and operating data-intensive backend or data engineering systems at scale. Strong hands-on expertise in Python , including development of production-grade data processing and backend services. Strong experience designing and building scalable data ingestion and ETL/ELT pipelines for large and heterogeneous datasets. Sound data engineering instincts, including data modeling, storage design, schema evolution, query optimization, caching strategies, and selecting appropriate batch or streaming processing patterns. Hands-on experience with Apache Spark or Databricks for distributed data processing. Experience with workflow orchestration technologies such as Prefect, Apache Airflow , or equivalent. Strong understanding of data modeling, schema design, validation strategies, data transformation, and data quality management . Experience designing solutions for data deduplication, entity resolution, data enrichment, classification, or record linkage . Experience with both relational and document-oriented databases; practical knowledge of technologies such as MongoDB or comparable NoSQL platforms. Experience with search technologies such as OpenSearch, Elasticsearch , or comparable solutions. Strong AWS experience, including services such as S3, ECS/EKS, Lambda , or equivalent cloud-native technologies. Hands-on experience with Docker, Kubernetes, CI/CD , and operating cloud-native workloads in production. Strong understanding of production data pipeline concerns including reliability, fault tolerance, observability, monitoring, alerting, and incident response . Experience establishing and maintaining data governance standards , schemas, validation rules, and repeatable data refinement processes. Practical experience using AI-assisted software engineering tools as part of the regular development lifecycle. Strong ownership mindset and ability to independently identify data or engineering problems, propose solutions, implement them, and operate them in production. Strong communication skills and ability to collaborate directly with engineering, analytics, product, data science, and business stakeholders. Professional English sufficient for direct collaboration with U.S.-based teams. Experience working with healthcare data, HealthTech platforms, or healthcare interoperability . Knowledge of FHIR , particularly resources such as Practitioner, Organization, PractitionerRole, Endpoint, and Location. Experience integrating data from EHR/EMR systems, healthcare registries, provider networks , or similar complex data ecosystems. Experience designing data platforms handling PHI/PII or other regulated and sensitive information . Familiarity with HIPAA-related data protection and security considerations. Nice to Have Experience building AI-powered data processing solutions , particularly entity resolution, relationship inference, classification, enrichment, anomaly detection, or data quality scoring. Practical experience integrating LLMs into production data workflows , including evaluation, reliability, latency, cost, and data-protection considerations. Experience with AI engineering tools such as Claude Code, GitHub Copilot, Cursor , or similar platforms. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills Python Spark

2GIS CDP — это внутренняя Customer Data Platform, лежащая в основе стратегии развития всего 2ГИС на ближайшие годы. CDP объединяет данные из десятков источников, строит единые пользовательские профили, рассчитывает метрики, интересы и модели поведения, помогает запускать real-time персонализацию прямо в продукте и управлять персонализированной рекламой и коммуникацией. Это стартап внутри большой компании — со свободой в архитектуре и технологиях, с задачами уровня highload и с реальным влиянием на бизнес-результаты. О команде Мы объединяем инженеров, аналитиков и ML-специалистов, которые строят систему, меняющую подход к данным в 2ГИС. Работаем с большими объемами событий, продумываем архитектуру под масштаб и надежность, ценим простые и элегантные решения. Каждый в команде влияет на архитектуру, подходы и направление развития CDP. Наш стек Backend: Go, gRPC Frontend: TypeScript, React Autotests: Python, Playwright, Allure Infrastructure: Kubernetes, Kafka, ClickHouse, Spilo/PostreSQL, Spark, Airflow. Стек только формируется — ты сможешь повлиять на его развитие и архитектуру. Тебе предстоит Повысить эффективность пайплайнов для расчета с daily-признаков на основе batch процессинга. Создать эффективный пайплайн для расчёта realtime-признаков на основе Kafka‑топиков. Проектировать и разрабатывать сервисы, обрабатывающие миллиарды событий пользователей. Решать сложные инженерные задачи: расчеты метрик, построение витрин. Работать с потоками данных и интеграциями между CDP и другими системами 2ГИС. Влиять на архитектурные решения и качество кода. Работать в распределенной команде, взаимодействуя с аналитиками, продактами и инженерами других направлений. Ждем от тебя Опыт работы с highload-системами. Опыт проектирования архитектуры данных или платформенного кода. Опыт работы с Kafka, ClickHouse или другими системами потоковой и аналитической обработки данных. Хорошо понимает, как работает Spark и умеет его готовить. Хорошо владеешь одним из языков программирования (например, Python или Scala). Самостоятельность и проактивность — ты не ждешь постановок, а предлагаешь решения. Желание разбираться в бизнес-логике и создавать продукт, а не просто писать код. Будет плюсом: Опыт работы с Airflow. Опыт анализа данных с использованием SQL. Знание инструментов мониторинга и автоматического контроля качества данных (Data Quality, Data Contracts). Опыт построения Data Lineage и работы с Data Catalog. Понимание подходов к персонализации, сегментации или real-time аналитике. Понимание, как работает S3 хранилище. Почему это круто Масштаб: миллионы пользователей, миллиарды событий, сотни интеграций. Рост: CDP — стратегическое направление, растем быстро и даем расти команде. Свобода: минимум бюрократии, максимум ответственности. Видимый результат: все, что ты делаешь, влияет на продукт, коммуникации и рекламу 2ГИС. Хочешь строить внутренний «мозг» 2ГИС? Присоединяйся к команде CDP.

Задачи: — Реализовывать репликацию данных — Разрабатывать ETL-процессы для интеграционных задач и тестировать их — Декомпозировать задачи, оценивать длительность и трудоемкость каждого этапа — Анализировать и формализовать требования заказчика — Собирать прототип решения — Анализировать качество данных — Писать проектную документацию (FSD, BRD, регламент, Admin Guide, User Guide) — Тестировать функционал и передавать заказчику — Выполнять ad-hoc выгрузки по требованиям заказчика Требования: — Уверенное владение SQL — Опыт работы с Python — Опыт работы с Apache Spark, Hadoop\S3\S3-like, Airflow — Навыки декомпозиции сложных задач и управления приоритетами — Способность создавать понятную и структурированную техническую документацию Будет плюсом: — Опыт работы с Parquet\ORC, Apache Iceberg — Опыт работы с Kafka — Знание архитектуры Data Vault Условия: — Внутренние семинары, внутренние митапы — ДМС со стоматологией для сотрудников и скидку на покупку ДМС для ближайших членов семьи — Техника для комфортной работы — Сессии профессионального развития персонала, результатом которой является план индивидуального развития каждого сотрудника

💎 Держать стабильность и отказоустойчивость инфраструктуры финтех-продукта: OVHcloud как основная площадка плюс AWS и Azure, Linux (RHEL 9 / AlmaLinux), Nginx, PHP, Percona MySQL / Galera, Redis, RabbitMQ, NFS / S3, мониторинг и алертинг через Datadog, Sentry, Pingdom и OpsGenie.

Location: Москва Создаем поисковый сервис для ответа на запросы пользователей на естественном языке. Ломаем барьер между статичными знаниями языковой модели и постоянно меняющимся миром. Предоставляем GigaChat доступ к актуальной информации, чтобы пользователи получали точные ответы на любые вопросы, включая вопросы о свежих новостях и событиях. Обязанности * разработка и развитие backend сервисов на Python и поискового индекса * интеграции с различными источниками данных (базы, стриминговые системы, аналитические движки, llm-агенты) * работа над производительностью, отказоустойчивостью и масштабируемостью * участие в код-ревью, формирование best practices команды Требования * опыт коммерческой разработки на Python от 3 лет * хорошее знание FastAPI / Flask / Django REST Framework * опыт работы с SQL и одной из СУБД (PostgreSQL, ClickHouse, S3 и др.) * Опыт работы с OpenSearch/ElasticSearch * понимание принципов построения REST API * опыт работы с брокерами сообщений (Kafka / RabbitMQ) * знание Git, Docker, CI/CD * базовые знания систем кэширования (Redis) будет плюсом * понимание того, как работает поиск, полнотекстовые и векторные индексы будет плюсом * опыт написания тестов (pytest/unittest). Условия * комфортный современный офис рядом с м. Кутузовская * гибридный формат работы * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * система обучения для профессионального и карьерного развития * расширенный полис ДМС с первого дня работы и страхование для семьи * программа ипотеки для сотрудников * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбер.

Задачи: — Валидация процессов загрузки данных — Проверка корректности скачивания данных из внешних источников (БКИ, ЦБ, ФНС и др.) — Контроль раскладки данных по целевым таблицам в S3/Iceberg — Подтверждение обработки 100% входящего объёма данных — Тестирование механизмов обновления: отсутствие дубликатов при повторной загрузке — Блокировка записей с аномалиями (ошибки источника, некорректные форматы) — Анализ документации (ТЗ, мэппинги) для проектирования тест-кейсов Требования: — Опыт интеграции внешних источников (БКИ, ФНС, ЦБ) — Практическое знание SQL: написание проверочных запросов, анализ трансформаций, выявление расхождений — Понимание архитектуры Lakehouse (S3, Iceberg) и слоёв хранения (RAW/ODS/DDS) — Базовое чтение кода на Python (для анализа скриптов обработки данных) — Знание Big Data-инструментов: Airflow (мониторинг задач), Spark (понимание логики обработки), S3/Hadoop Условия: — Оформление по ТК РФ c полной «белой» историей