Вакансии

🕹 Список обязанностей: — Развитие и оптимизация инфраструктуры DataOps, внедрение современных архитектурных решений и автоматизация инфраструктурных процессов; — Участие в разработке отказоустойчивого кластеризованного решения ClickHouse в on-prem-среде;

We’re looking for a Senior DataOps Engineer to help operate, scale, and improve the data platforms that support Oportun’s analytics, engineering, and business teams. This role will focus on Databricks, AWS, data pipelines, databases, observability, automation, and production support.

В роли предстоит развивать DWH и ML-платформу, строить пайплайны от сбора данных до деплоя моделей, настраивать мониторинг и CI/CD. Сейчас усиливаем Data/ML-направление и ищем Senior MLOps / DataOps инженера, который поможет выстроить стабильную и масштабируемую инфраструктуру для работы с данными и моделями.

Поддерживать и развивать инфраструктуру дата‑платформы: HDFS, Spark, ClickHouse, Airflow и др. Запускать и эксплуатировать Ceph‑кластер с высокими требованиями к SLA.

Location: Malta The Wow Are you passionate about data, technology and finding smarter ways to make systems run better? We're looking for a Data Operations Engineer to join our Data & AI organization in Malta, helping operate and continuously improve the data platforms that support our international business. You'll work with modern data technologies, including Snowflake, Apache Airflow and AWS , ensuring reliable data operations while contributing to improvements in monitoring, automation and platform stability. This role goes beyond day-to-day operations. We encourage our engineers to challenge existing processes, explore new technologies and implement improvements that make a real difference. From enhancing observability to developing automation and AI-assisted solutions, you'll have opportunities to actively shape how our data operations evolve. You'll collaborate with experienced Data Engineering, BI and DevOps teams, applying and expanding your technical skills while gaining valuable experience with business-critical data platforms. A taster of what you will be involved with: Data Platform Operations: Ensure the smooth daily operation of our data platforms, pipelines and reporting services, supporting reliable data processing and availability across the business. Operational Improvements: Identify opportunities to simplify processes, improve data reliability, reduce manual effort and enhance the efficiency of our operations. Automation and Innovation: Develop scripts, automated checks and AI-assisted solutions to streamline operational activities and improve platform reliability. Monitoring and Observability: Work with monitoring and alerting solutions, improving visibility into data pipelines and platform health to detect issues before they impact the business. Production Releases and Changes: Support deployments, data processing activities and operational changes, helping maintain stable and reliable production environments. Incident Management and Troubleshooting: Investigate and resolve technical issues, including pipeline failures, data inconsistencies and processing delays, collaborating with engineering teams when needed. Participate in a scheduled, compensated out-of-hours on-call rotation to help maintain service reliability. Cross-Team Collaboration: Work closely with Data Engineers, BI Developers and DevOps Engineers, share knowledge, document solutions and contribute to continuous improvement initiatives. What we are looking for: Must haves: Experience in Data Engineering, Data Operations, production support, database support or a similar technical role. Strong SQL skills , including writing and troubleshooting queries, working with joins and aggregations, investigating data inconsistencies and validating data. Good understanding of data processing concepts, data pipelines, transformations and dependencies. Experience troubleshooting technical issues using queries, logs, monitoring information or other diagnostic tools. Familiarity with production operations, incident management and troubleshooting practices. Strong analytical and problem-solving skills, with a structured approach to investigating issues and identifying root causes. Good written and spoken English, a collaborative mindset, ownership and willingness to learn. Nice to have: Snowflake or other cloud data warehouses , including data processing, querying and troubleshooting. Workflow orchestration, scheduling and data pipeline operations. Cloud environments and cloud-based data services. Monitoring, logging, alerting and observability solutions. Scripting and automation using Python, Bash or similar languages. Production deployments, change management or CI/CD processes. What we offer Much like riding a rollercoaster, sometimes life at Betsson can be lightning fast with twists and turns but always FUN! Then again, what else would you expect from a business 75% millennial and 1700 strong, spread across 7 offices with 900 based out of our Malta HQ alone! We recognise it may not be for the faint-hearted, but if you’re a go-getter, initiator and adrenaline junkie, always striving to push the boundaries and challenge yourself, then you’ll fit right in. Challenge accepted? By submitting your application, you understand that your personal data will be processed as set out in our Privacy Policy

Задачи: — Работа с распределёнными системами, MPP, инфраструктурой баз данных. — Влияние на то, как все работает вместе. Условия: — Возможность работать удалённо или в офисе с релокацией за счёт компании. — Поддержка профессионального развития. — Свобода в технических решениях.

Задачи: — Разрабатывать кластеризованный on-premise build ClickHouse для собственной cloud-инфраструктуры — Внедрять, масштабировать и поддерживать ClickHouse-кластеры в production — Развивать DB-related инфраструктуру Data-платформы — Автоматизировать инфраструктурные процессы и создавать внутренние tooling-решения — Развивать и интегрировать ролевые модели для ClickHouse, Snowflake, PostgreSQL и других баз данных — Проектировать naming conventions и пользовательские ролевые модели для баз данных — Работать с MPP и distributed query stack, включая Trino, Greenplum, Vertica, StarRocks и другие технологии — Участвовать в развитии производительности, надежности и масштабируемости Data-инфраструктур Требования: — 5+ лет опыта в DevOps / SRE / DataOps — Глубокая практическая экспертиза в ClickHouse и опыт работы с ним в production — Сильное понимание distributed systems, networking, storage и performance — Опыт production troubleshooting и низкоуровневого тюнинга Linux / *nix-систем — Опыт разработки инструментов автоматизации, предпочтительно на Python и/или Go — Глубокое понимание основных принципов, технологий и инструментов Cybersecurity / AppSec — Опыт работы с Karpenter — Опыт оптимизации расходов AWS с использованием Kubecost, Infracost, AWS tagging и других подходов — Опыт работы с ingress, балансировкой и терминацией трафика: Traefik, Istio, Nginx, SSL/TLS — Опыт работы с Identity Management решениями: Authentik, Keycloak, Okta или аналогами — Опыт работы с VPN-решениями: Pritunl, OpenVPN, WireGuard, Fortinet или аналогами — Глубокое понимание как минимум одной аналитической БД, MPP-системы или distributed query engine: ClickHouse, StarRocks, Trino, Greenplum, Doris, DuckDB, Vertica или аналогов Условия: — Работа со сложной Data/ML-инфраструктурой и возможность влиять на ее архитектуру и развитие — Высокий уровень технической автономии и среда без микроменеджмента — Гибкий формат работы: удаленно или из офиса — Гибкое начало рабочего дня с 9:00 до 11:00 — Поддержка релокации за счет компании — Компенсация спорта и занятий английским языком — Сессии с психологом и доступ к корпоративной библиотеке — Возможности для профессионального развития и обмена технической экспертизой — Командные мероприятия, тимбилдинги и мастер-классы

Задачи: — Развивать и поддерживать IT-инфраструктуру, обеспечивать стабильность и отказоустойчивость систем. — Настраивать и сопровождать процессы CI/CD, автоматизировать развёртывание и эксплуатацию сервисов. — Работать с контейнеризацией и оркестрацией на базе Docker и Kubernetes. — Автоматизировать инфраструктурные и эксплуатационные задачи с использованием Ansible, Bash и Python. — Администрировать базы данных, обеспечивать резервное копирование, восстановление и мониторинг. — Поддерживать и оптимизировать процессы загрузки, преобразования и обработки данных (ETL). — Участвовать в развитии хранилищ данных (DWH) и витрин данных. — Настраивать мониторинг, алертинг и диагностику инфраструктуры и сервисов. — Анализировать и устранять проблемы производительности, загрузки и обработки данных. — Использовать AI-инструменты и AI-агентов для автоматизации рутинных DevOps-задач и повышения эффективности работы. Требования: — Опыт работы в DevOps и/или Data Engineering от 4 лет с практическими навыками в обоих направлениях. — Уверенное владение Linux (Ubuntu/Debian, CentOS/RHEL). — Опыт работы с Docker, Kubernetes и Helm. — Практический опыт работы с Ansible и CI/CD на базе GitLab. — Навыки автоматизации с использованием Bash и Python. — Уверенное владение SQL и опыт работы с PostgreSQL. — Опыт работы с одной или несколькими СУБД: PostgreSQL, ClickHouse, Greenplum. — Понимание принципов построения хранилищ данных (DWH) и организации ETL-процессов. — Опыт работы с Apache NiFi и/или Apache Airflow. — Опыт настройки мониторинга и алертинга (Grafana, Prometheus или аналоги). — Понимание сетевых технологий и протоколов TCP/IP, HTTP, DNS. — Умение самостоятельно решать технические задачи и взаимодействовать с проектной командой. Будет плюсом: — Практический опыт разработки ETL-процессов, хранилищ и витрин данных. — Опыт работы с Python-библиотеками SQLAlchemy и Pandas. — Знакомство с продуктами Arenadata (ADB, ADS, ADH). — Опыт работы с Hadoop, PySpark или Apache Kafka. — Опыт работы с Terraform и OpenStack. — Опыт настройки высокодоступных и масштабируемых систем. — Понимание принципов Data Quality и опыт автоматизации проверок качества данных. — Практический опыт использования AI/LLM-инструментов и AI-агентов для автоматизации инженерных задач.

Задачи: — Развивать и поддерживать инфраструктуру DWH — Строить и развивать CI/CD-процессы для data и ML-разработки — Разрабатывать и поддерживать пайплайны обработки данных и оркестрации (Airflow) — Реализовывать end-to-end ML-пайплайны: от сбора данных до деплоя и мониторинга моделей — Проектировать и развивать MLOps-платформу (выбор и интеграция инструментов) — Разворачивать и поддерживать инфраструктуру для ML-задач: (JupyterHub + GPU, Airflow, ClickHouse, PostgreSQL, S3 и др.) — Взаимодействовать с ML- и Data-инженерами для вывода решений в production — Настраивать мониторинг и алёртинг: качество данных, стабильность пайплайнов, ресурсы — Автоматизировать рутину и развивать self-service инструменты для data-команды Требования: — Уверенный опыт с Docker и Kubernetes — Опыт работы с Airflow (или аналогами оркестрации) — Практика построения CI/CD для data/ML пайплайнов — Хорошие знания Python, SQL и Git — Опыт развёртывания ML-инфраструктуры (GPU-кластеры, хранилища, orchestration) — Опыт работы с облачными платформами — Понимание принципов CI/CD и автоматизации деплоя — Опыт работы с API и понимание highload-систем — Опыт работы со стримингом данных (Kafka / аналоги) — Практика настройки мониторинга и логирования — Уверенная работа в Linux — Будет плюсом: Опыт внедрения систем управления экспериментами (MLflow, ClearML)

Задачи: — Разработка кластеризованного on-prem билда ClickHouse под собственную облачную инфраструктуру; — Внедрение, масштабирование, поддержка; — Развитие DB-related инфраструктуры DAP; — Автоматизация, интеграция инструментов ролевых моделей: ClickHouse, SF, PostgreSQL и др.; — Нейминг конвеншн и пользовательские ролевые модели баз данных; — Работа с MPP-стеком: Trino, Greenplum, Vertica, StarRocks. Требования: — Опыт в позициях DevOps / SRE / DataOps от 5 лет; — Опыт написания автоматизации и tooling, предпочтительно на Python и Go; — Опыт production troubleshooting и низкоуровневого тюнинга ОС на базе *nix, преимущественно в облаке; — Глубокое понимание распределённых систем, сетей, хранилищ и производительности; — Глубокое понимание основных концепций, технологий и инструментов кибербезопасности (cybersec/appsec); — Опыт работы с Karpenter; — Опыт оптимизации затрат в AWS (Kubecost, Infracost, AWS теги и др.); — Опыт работы с termination трафиком, ingress и балансировщиками (Traefik, Istio, Nginx + сертификаты); — Опыт с Authentik или аналогами Keycloak/OKTA (управление идентификацией); — Опыт с VPN решениями (Pritunl {OpenVPN, WireGuard}, Fortinet и аналоги); — Желательно глубокое понимание хотя бы одной аналитической базы данных / MPP / распределённого движка запросов: ClickHouse, StarRocks, Trino, Greenplum, Doris, DuckDB, Vertica. Условия: — Рабочее место по выбору: офис в бизнес-центре класса «А» в Белграде (Сербия) или удалённая работа; — Гибкое начало рабочего дня с 9:00 до 11:00, 9-часовой рабочий день с часом на обед; — Частичная компенсация занятий в фитнес-зале и курсов английского, доступ к корпоративной библиотеке и консультации с психологом; — Поддержка при релокации: релокационный пакет в Белград; — Корпоративные мероприятия, выезды на природу, тимбилдинги и мастер-классы; — Качественный профессиональный опыт, развитие навыков и комфортная рабочая атмосфера.

Location: Portugal Workplace: remote *ALL CANDIDATES MUST BE LOCATED IN PORTUGAL* About Intermedia Are you looking for a company where YOUR VOICE is heard? Where can you MAKE A DIFFERENCE? Do you THRIVE in a FAST-PACED work environment? Do you wake every morning EXCITED to work with GREAT PEOPLE and create SUCCESS TOGETHER? Then Intermedia is the place for you. Intermedia has established itself as a leading provider of cloud communications and collaboration tech that allows companies to connect better. We have a strong track record of growth, profitability, and creating an environment where everyone matters. Everyone. While we are fast-paced and admittedly a bit intense, we promise that you won’t be bored. You will find Intermedia is a place where you can indulge your passion for creating and supporting great cloud technology. What’s more, we always look to promote from within and have many employees who have been with us 10, 15, and 20+ years! Culture at Intermedia is built on teamwork and transparency. We hold each other accountable and always have each other’s back! While primarily remote, this role requires occasional visits to the office in Coimbra or in Aveiro. We plan to open an office in Porto in the future. This approach gives team members the flexibility to work remotely while also coming together in the office for collaboration and teamwork. Are you ready to make your mark? About the Role We are looking for a Site Reliability Engineer (SRE) to improve the reliability of our AI and analytics platforms and the services that depend on them. As Intermedia expands its global product deployments, this role will strengthen SRE practices across production infrastructure, data pipelines, machine-learning services, customer-facing analytics, and AI-powered Voice and Unified Communications capabilities. You will partner with AI, data, product, and platform teams to build scalable, observable systems that deliver dependable insights and resilient customer experiences. What you will be doing: Run and improve production environments that support AI and AI workloads, data pipelines, analytics applications, and customer-facing services. Build software and automation to manage cloud infrastructure, data platforms, model-serving infrastructure, and application services. Define and measure service level indicators, service level objectives, and error budgets for AI and analytics services, including availability, data freshness, pipeline completion, and inference latency. Build end-to-end observability that correlates metrics, logs, and traces with data-quality signals, AI-service performance, and customer impact. Monitor and optimize the reliability, performance, capacity, and cost of batch and streaming workloads, analytics queries, and inference services. Partner with data engineering and machine-learning teams to make ingestion, transformation, feature, training, deployment, and reporting workflows production-ready. Automate CI/CD and production-readiness checks for data pipelines, model and prompt releases, schema changes, analytics applications, and dashboards. Detect and resolve data-quality incidents involving missing, stale, delayed, or anomalous data, schema drift, and broken lineage or dependencies. Design and test graceful degradation, dependency isolation, retry and fallback patterns, and recovery procedures for impaired AI, data, or downstream services. Improve the reliability of AI-powered Voice and Unified Communications capabilities such as speech recognition, transcription, summarization, intelligent routing, conversational assistance, and text-to-speech. Establish operational monitoring for model and AI-service behavior, including latency, throughput, error rates, drift indicators, and changes in output quality. Plan capacity and run performance, load, and resilience tests across compute-intensive AI workloads, distributed data processing, and analytics services. Lead incident response and post-incident improvement for AI and analytics services, using measurable actions to reduce recurrence and recovery time. Support secure and reliable access to cloud storage, processing, and query services used by analytics products and internal decision-making. Reduce operational toil and improve engineering productivity through platform tooling, runbooks, self-service automation, and clear operational standards. What you will bring to the role: Bachelor's degree in computer science, data engineering, software engineering, or another technical or scientific discipline, or equivalent practical experience. 4-7 years of experience in production operations, systems engineering, SRE or DevOps, software deployment, and maintenance of distributed production systems. Experience with cloud infrastructure, containers, Kubernetes, distributed systems, and scalable compute and storage services. Experience operating data processing, orchestration, storage, or analytics technologies, such as Kafka, Spark, Airflow, dbt, data warehouses, or comparable cloud services. Ability to use metrics, logs, traces, data-quality checks, freshness indicators, lineage, and service-level indicators to diagnose complex production issues. Experience with CI/CD, DataOps or MLOps practices, automated testing, controlled rollout, and rollback of data and AI service changes. Strong troubleshooting skills across Linux, applications, networks, APIs, data pipelines, and distributed service dependencies, with attention to security and access controls. Strong analytical problem-solving and cross-functional communication skills, with a proactive approach to reliability, performance, and continuous improvement. Diversity Inclusion and Equal Opportunity We hire, promote, and compensate employees based on their ability to perform their job responsibilities, without regard to race, color, creed, religion, sex, gender, marital status, national origin, ancestry, age, citizenship, physical or mental disability, sexual orientation, or any other basis protected by applicable law (collectively referred to in our Code of Conduct as “Protected Classes”). We do not tolerate employment discrimination in the workplace, and we are committed to making reasonable accommodations for identified disabilities or other limitations as required by all applicable laws. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Location: Portugal Workplace: remote *ALL CANDIDATES MUST BE LOCATED IN PORTUGAL* About Intermedia Are you looking for a company where YOUR VOICE is heard? Where can you MAKE A DIFFERENCE? Do you THRIVE in a FAST-PACED work environment? Do you wake every morning EXCITED to work with GREAT PEOPLE and create SUCCESS TOGETHER? Then Intermedia is the place for you. Intermedia has established itself as a leading provider of cloud communications and collaboration tech that allows companies to connect better. We have a strong track record of growth, profitability, and creating an environment where everyone matters. Everyone. While we are fast-paced and admittedly a bit intense, we promise that you won’t be bored. You will find Intermedia is a place where you can indulge your passion for creating and supporting great cloud technology. What’s more, we always look to promote from within and have many employees who have been with us 10, 15, and 20+ years! Culture at Intermedia is built on teamwork and transparency. We hold each other accountable and always have each other’s back! While primarily remote, this role requires occasional visits to the office in Coimbra or in Aveiro. We plan to open an office in Porto in the future. This approach gives team members the flexibility to work remotely while also coming together in the office for collaboration and teamwork. Are you ready to make your mark? About the Role We are looking for a Site Reliability Engineer (SRE) to improve the reliability of our AI and analytics platforms and the services that depend on them. As Intermedia expands its global product deployments, this role will strengthen SRE practices across production infrastructure, data pipelines, machine-learning services, customer-facing analytics, and AI-powered Voice and Unified Communications capabilities. You will partner with AI, data, product, and platform teams to build scalable, observable systems that deliver dependable insights and resilient customer experiences. What you will be doing: Run and improve production environments that support AI and AI workloads, data pipelines, analytics applications, and customer-facing services. Build software and automation to manage cloud infrastructure, data platforms, model-serving infrastructure, and application services. Define and measure service level indicators, service level objectives, and error budgets for AI and analytics services, including availability, data freshness, pipeline completion, and inference latency. Build end-to-end observability that correlates metrics, logs, and traces with data-quality signals, AI-service performance, and customer impact. Monitor and optimize the reliability, performance, capacity, and cost of batch and streaming workloads, analytics queries, and inference services. Partner with data engineering and machine-learning teams to make ingestion, transformation, feature, training, deployment, and reporting workflows production-ready. Automate CI/CD and production-readiness checks for data pipelines, model and prompt releases, schema changes, analytics applications, and dashboards. Detect and resolve data-quality incidents involving missing, stale, delayed, or anomalous data, schema drift, and broken lineage or dependencies. Design and test graceful degradation, dependency isolation, retry and fallback patterns, and recovery procedures for impaired AI, data, or downstream services. Improve the reliability of AI-powered Voice and Unified Communications capabilities such as speech recognition, transcription, summarization, intelligent routing, conversational assistance, and text-to-speech. Establish operational monitoring for model and AI-service behavior, including latency, throughput, error rates, drift indicators, and changes in output quality. Plan capacity and run performance, load, and resilience tests across compute-intensive AI workloads, distributed data processing, and analytics services. Lead incident response and post-incident improvement for AI and analytics services, using measurable actions to reduce recurrence and recovery time. Support secure and reliable access to cloud storage, processing, and query services used by analytics products and internal decision-making. Reduce operational toil and improve engineering productivity through platform tooling, runbooks, self-service automation, and clear operational standards. What you will bring to the role: Bachelor's degree in computer science, data engineering, software engineering, or another technical or scientific discipline, or equivalent practical experience. 4-7 years of experience in production operations, systems engineering, SRE or DevOps, software deployment, and maintenance of distributed production systems. Experience with cloud infrastructure, containers, Kubernetes, distributed systems, and scalable compute and storage services. Experience operating data processing, orchestration, storage, or analytics technologies, such as Kafka, Spark, Airflow, dbt, data warehouses, or comparable cloud services. Ability to use metrics, logs, traces, data-quality checks, freshness indicators, lineage, and service-level indicators to diagnose complex production issues. Experience with CI/CD, DataOps or MLOps practices, automated testing, controlled rollout, and rollback of data and AI service changes. Strong troubleshooting skills across Linux, applications, networks, APIs, data pipelines, and distributed service dependencies, with attention to security and access controls. Strong analytical problem-solving and cross-functional communication skills, with a proactive approach to reliability, performance, and continuous improvement. Diversity Inclusion and Equal Opportunity We hire, promote, and compensate employees based on their ability to perform their job responsibilities, without regard to race, color, creed, religion, sex, gender, marital status, national origin, ancestry, age, citizenship, physical or mental disability, sexual orientation, or any other basis protected by applicable law (collectively referred to in our Code of Conduct as “Protected Classes”). We do not tolerate employment discrimination in the workplace, and we are committed to making reasonable accommodations for identified disabilities or other limitations as required by all applicable laws. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Location: Montevideo, Uruguay; Remote.AR, Remote.LATAM-country; Remote.CO, Colombia; Rosario, Remote.LATAM-country We are looking for a hands-on Data Engineer (Middle/Senior) to design, build, and maintain reliable, scalable pipelines that keep information timely, clean, secure, and well-structured for downstream consumers. This is an execution-focused role combining pipeline development, query and cost optimization, data governance, and production monitoring. The engineer will work closely with business, analytics, and data science teams to make data available and trustworthy across the organization. The Data & AI chapter of the Passenger Journey builds and operates the data foundation that turns raw data into trusted, strategic assets for analytics, product, and business teams. The team works on Google Cloud Platform (GCP) under Agile and DataOps practices, with a tech stack centered on BigQuery and SQL, Dataform (including assertions) for transformation, and Python (Pandas) for processing and automation. Pipelines run on Cloud Run, Cloud Run Jobs, Dataflow, Pub/Sub, Cloud Storage, Cloud SQL, and Cloud Scheduler, with Git/GitLab, CI/CD, and Terraform for delivery, and IAM and policy tags for access control. Data is organized under a medallion architecture (Bronze, Silver, Gold), with cost and performance optimization (FinOps) treated as a first-class concern. Design, implement, and maintain reliable, scalable ingestion and transformation pipelines that ensure data quality, integrity, and availability for business and analytics. Optimize processing and storage by reducing execution time and costs (FinOps) across pipelines and queries to maximize the value of data. Apply data governance standards, including quality, naming conventions, cataloging, and a medallion architecture (Bronze, Silver, Gold), to ensure consistency and traceability. Protect sensitive data through role-based access control (IAM) and policy tags, ensuring compliance with applicable regulations and standards (GDPR, LGPD, ISO, and local regulations). Monitor pipelines, respond to incidents, and adapt them to new business requirements while meeting availability and performance SLAs. Enable controlled, cross-functional access to data for broad consumption. 3+ years of proven experience as a Data Engineer or in a similar role. Strong SQL skills and hands-on experience with BigQuery, including query optimization, partitioning, and clustering. Experience building and maintaining ELT/ETL pipelines and data models with Dataform (or a similar framework, such as dbt, with skills readily transferable to Dataform), including assertions. Experience with Python for data processing and automation (Pandas). Solid GCP experience across Cloud Run / Cloud Run Jobs, Dataflow, Pub/Sub, Cloud Storage, Cloud SQL, and Cloud Scheduler. Knowledge of medallion architecture (Bronze/Silver/Gold) and sound data-modeling fundamentals. Knowledge of data governance and compliance, including IAM, policy tags, and regulatory awareness (GDPR, LGPD, ISO). Experience with Git/GitLab, CI/CD, and Terraform for delivery and infrastructure as code. Experience with pipeline monitoring and observability (Cloud Monitoring; Grafana is desirable). Exposure to GenAI-assisted development and tooling, including prompt engineering, OpenAI API/SDK, Vertex AI, and MCP (desirable). Experience with API development using FastAPI / REST services (desirable). Experience with BI and data visualization tools such as Looker Studio or Google Data Studio (desirable). Ability to communicate effectively with technical and non-technical stakeholders, and experience working in Agile environments. Fluency in Spanish (the team's working language) and intermediate English proficiency for documentation and international collaboration.

Location: Москва Мы - команда, создающая **комплексную систему противодействия мошенничеству** и обеспечивающая online/offline безопасность миллионов клиентов банка 24/7/365, предоставляя инструменты **собственной разработки** для: * Построения графа связей (позволяет проанализировать не только объекты и их свойства, но также их связи с другими объектами различных уровней и характеристик и применяется для получения дополнительных знаний об объекте за счет извлечения знаний о его окружении, выявления наиболее значимой информации, центров влияния, групп связанных объектов, цепочек) * Геопространственой аналитики: анализа локаций, построения маршрутов и тепловых карт * Выявления и анализа попыток мошенничества и иных отклонений * Портфеля технологичных сервисов накопления и обработки больших объемов данных со сложной структурой Мы находимся на передовой технологических инноваций, соединяя возможности ИИ, современные технологии и потребности общества. Наше направление AI-трансформации — это стратегическая инициатива по интеграции LLM-агентов и мультиагентных систем в собственную аналитическую платформу: * AI-решения для глубокого анализа данных * Набор AI Tools, дающих агентам доступ к инструментам и сервисам платформы * Собственная no-code/low-code платформа для оркестрации AI-агентов и автоматизации рабочих процессов * Интеграция с внутренними LLM-шлюзами и средами исполнения агентов * RAG-системы для работы с корпоративными базами знаний и методологиями Наш передовой технологический стек: * Storage - Hadoop, Cassandra, ClickHouse, Elasticsearch, FastGraph, PostgreSQL * Big Data Engineering- Scala, Spark, Flink * Backend - GO (GIN), Scala (ZIO), Kubernetes (OpenShift, DropApp) * Fronted - React, Redux (Redux ToolKit, RTK Query), Typescript, jest. Библиотеки: react-force-graph, leaflet * AI - Python (LangChain, LangGraph, Harness), GO (mcp-go), Typescript (no code platform), ai-coding (gigacode cli, claude, codex), RAG\\GraphRag (PostgreSQL, Elasticsearch, Qdrant) * QA - Java, TestNG, Selenium, Maven, Allure * DevOps - Docker, Helm, Jenkins Обязанности * Проектирование и анализ архитектуры технического решения совместно с командой разработки * Разработка и согласование концепции, проектной документации и технической документации, описание API, ведение документации в Confluence * Развитие направления мультиагентных решений обеспечивая полный цикл реализации * Проведение исследовательских работ и тестирование новых подходов и техник AI * Анализ источников данных, разработка моделей данных, логики алгоритмов и интеграций * Документирование и обеспечение соблюдения правил сбора, хранения и использования данных * Участие в полном цикле разработки и внедрения Требования * Умение быстро погружаться в исследуемую область и оперативно переключаться на новое направление * Навыки интеграции решений на основе ML/AI в реальные производственные системы * Опыт проектирования логической и физической моделей данных. Языки SQL: понимание работы ETL-инструментов, умение писать SQL-запросы различной сложности * Знание форматов JSON/XML и навыки проектирование REST API * Способность обрабатывать и структурировать большой объем сложной информации, доступно и наглядно ее презентовать * Сбор, анализ и документирование бизнес-требований, описание use case, генерация идей, проработка технических решений, интеграционных взаимодействий * Коммуникативные навыки, достаточные для выстраивания конструктивного взаимодействия со смежными подразделениями и внутри команды Будет плюсом * Понимание ключевых алгоритмов и подходов в AI/GenAI (LLM, vector search, NLP, context engineering и др.) * Понимание архитектуры AI/GenAI решений, LLM, RAG, BI и DataOps * Наличие опыта разработки собственных библиотек и инструментов для AI * Опыт успешного внедрения AI-решений, знание инструментов AI на рынке * Опыт программирования на любом языке и способность анализировать код * Владение инструментами Big Data (Hadoop, AirFlow, Spark, Kafka) * Понимание принципов работы NoSQL баз данных (Cassandra, ClickHouse, ElasticSearch, Qdrant, Neo4j) Условия * Комфортный современный офис (ст.м.Кутузовская) * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

-Проектировать и разрабатывать новые, а также поддерживать существующие data pipeline’и в облачной среде. -Заниматься тюнингом и оптимизацией производительности пайплайнов (написание эффективного кода, работа с "горячими" точками, распределенные вычисления).

Location: United Kingdom We are EnerMech, a specialist service company that delivers safe, integrated solutions for complex energy projects. For over 50 years, we've been energizing our clients across the world with unrivalled expertise, equipment, and technology that supports the entire asset life-cycle - offshore and on land. We enable progress through our three global business lines: Energy Solutions, Infrastructure & Industrial Solutions, and Lifting Solutions. Within these areas, we offer a wide range of services, including cranes, lifting, fluid power, training, equipment rental, pipeline and subsea, process, and valves - all designed to help our clients optimize performance, enhance reliability, and improve efficiency. With a focus on operational excellence, we deliver value through our customized integrated solutions. This approach reduces risk and enhances efficiencies making us a leading and trusted partner every step of the way. The Role & Responsibilities The role will be responsible for taking technical ownership of key workstreams on EnerMech's Azure Databricks data platform, operating across the full platform stack: data modelling and pipeline development in Databricks, the underlying Azure infrastructure, and the CI/CD, DevOps and DataOps practices that keep the platform reliable, secure and scalable. The role holder operates with a high degree of autonomy, makes and documents architectural decisions, resolves complex platform issues, and is a technical point of contact for the global EBS Team, and business stakeholders. This is a fully remote role in the UK ,supporting our Enterprise Business Systems (EBS) function in the Mumbai Shared Service Centre. Key reponsibilities will include: Design, build, quality and reliable operation of assigned workstreams on the Azure Databricks data platform, from scoping through to production deployment. Integrity of the medallion data model (bronze/silver/gold) for assigned data domains, ensuring data is modelled, validated, documented and certified for downstream reporting and analytics. Build and optimise Delta tables and materialized views, with attention to performance at scale. Design and implement data quality frameworks (preferably DQX or equivalent), including quarantine/error handling and validation against data contracts. Define job-specific compute configurations appropriate to each workload, balancing performance and cost. Contribute to and troubleshoot Terraform-managed infrastructure (networking, storage, Key Vaults, Managed DevOps Pools, Dev Centers). Own and maintain Azure DevOps build and release pipelines, variable groups/libraries, and repository security, permissions and branch policies. Support environment-level Azure configuration, including subscription-level access, RBAC for user and pipeline (service principal) identities, and Terraform state backend management across multiple storage accounts and environments. Operate autonomously across a workstream, from scoping through to production deployment. Use AI-assisted tooling to support day-to-day development, validating outputs against authoritative sources (architecture decisions, technical leads, documentation) before acting on them. Communicate clearly with technical and non-technical stakeholders, including across time zones with colleagues in the UK, Americas, Middle East and Asia Pacific. The Requirements Essential Bachelor's degree in Computer Science, Engineering, Information Systems or a related discipline, or equivalent practical experience. Typically 6+ years in data engineering, including 3+ years hands-on with Azure Databricks in production. Demonstrated ownership of medallion architecture design and data modelling. Implemented data quality frameworks and data contracts in production. Implemented PII protection (masking, tokenisation or access tiering) across environments. Platform engineering experience: diagnosing infrastructure issues, not just consuming platform services. Track record of autonomous delivery, including direct stakeholder engagement. Databricks Certified Data Engineer Associate (minimum). Desirable Databricks Certified Data Engineer Professional. Microsoft AZ-400: Designing and Implementing Microsoft DevOps Solutions. Multi-environment Azure networking (VNet peering, DNS zone design, NAT Gateway). Migrating or standing up CI/CD pipelines, incl. introducing pipeline templates/standards. Governance and identity patterns (e.g. Entra ID, RBAC scoping). Applying regulatory frameworks (e.g. GDPR) to data platform design. Shared service centre or global delivery model experience, ideally in energy or industrial services.

Location: India Who We Are: Galaxy Digital Inc. (Nasdaq: GLXY) is a global leader in digital assets and data center infrastructure, growing the economy that runs on code. Galaxy delivers the onchain infrastructure that connects institutions to digital assets, including trading, advisory, asset management, staking, self-custody, and tokenization. Galaxy also develops and operates data center infrastructure to power AI and HPC workloads. Anchored by its Helios campus in Texas, Galaxy is building a multi-gigawatt pipeline of more than 5.7 GW of potential capacity, positioning it among the largest and fastest-growing data center developers in North America. The Company is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia. Additional information about Galaxy's businesses and products is available on www.galaxy.com . What We Value: We are a diverse team of free thinkers, and fast movers united to help investors and creators energize the global economy. We are looking for individuals who thrive in a culture of builders and overachievers and embrace high performance, transparent feedback, and a mission-first approach. Our culture shapes our way of working and gets us where we want to be. Seek Excellence. Be Selective To Be Effective. Be Highly Aligned, Loosely Coupled. Disagree Transparently. Encourage Independent Decision-Making. Build Dream Teams. Who You Are: You're a hands-on engineer with several years of experience building and operating production data platforms. You're fluent in Python or Java and comfortable across the modern data stack — AWS, Kubernetes, Terraform, Kafka, and Databricks/Spark. You care about reliability and developer experience, write clean and well-tested code, and like enabling other teams to move fast on infrastructure you own. You're curious about crypto and energized by working at the intersection of finance and emerging technology. What You’ll Do: Build and maintain the tooling and infrastructure that lets data champions ship pipelines autonomously Own monitoring, alerting, and dataops practices that keep the platform reliable as it scales Operate Kafka as the message broker powering cross-team event-driven architecture Deploy, own and maintain infrastructure components (services, OSS helm charts) with Terraform and Kubernetes Run high-throughput, low-latency processing on Databricks/Spark and cloud-native services on AWS Support dbt for transformations and Airflow (or similar) for orchestration across the platform Partner with product, analytics, and infrastructure teams on design and delivery of platform improvements Troubleshoo t production issues and drive the fixes Embrace and champion the thoughtful adoption of AI to improve team performance and business outcomes. Leverage AI tools (e.g., generative AI, automation platforms, data copilots) to improve productivity, decision-making, and output quality in your day-to-day work. What We’re Looking For: Bachelor’s or Master’s degree in Computer Science , Engineering, or related field 5+ years building data or platform engineering systems in production Strong coding skills in Python or Java Experience operating production data platforms on AWS and supporting downstream teams who build on them Hands-on with Kubernetes and Terraform Experience running Kafka (or a similar broker) in event-driven systems Working knowledge of Databricks/Spark, dbt, and Airflow Solid grasp of data modeling, data quality, and relational and non-relational databases (e.g., Postgres, SQL Server) Comfortable with CI/CD, testing frameworks, and observability tooling Bonus Points: Experience with d ashboarding technologies Experience with streaming engine ( flink , kdb ) Full lifecycle development of a commercial system, including: requirements definition, agile planning, releasing, and production support Experience in Crypto What We Offer : Competitive base salary and discretionary bonus Company-paid health and protective benefits for employees and their eligible dependents Free virtual coaching and counseling sessions Opportunities to learn about the Crypto industry Smart, entrepreneurial, and fun colleagues Employee Resource Groups *Benefits may vary depending on location. Apply now and join us on our mission to engineer a new economic paradigm. Galaxy respects diversity and seeks to provide equal employment opportunities to all employees and job applicants for employment without regard to actual or perceived age, race, color, creed, religion, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression (including transgender status), sexual orientation, marital or partnership or caregiver status, ancestry, national origin, citizenship status, disability, military or veteran status, protected medical condition as defined by applicable state or local law, genetic information or predisposing genetic characteristic, or other characteristic protected by applicable federal, state, or local laws and ordinances. We will endeavor to make a reasonable accommodation to the known limitations of a qualified applicant with a disability unless the accommodation would impose an undue hardship on the operation of our business. If you believe you require such assistance to complete the application process or to participate in an interview, please contact careers@galaxy.com.

Location: Russia You Are passionate about technology, wake up every morning to experiment, learn and develop new solutions! About Us At DBSync we provide the opportunity to use technology that creates innovative and next generation data integration products which helps our employees to cultivate their creativity and sense of belonging. DBSync is a leading provider for data integration and Data warehousing services for both cloud/SAAS-based-on-demand applications. We were incubated by Salesforce.com (as a part of Avankia), before getting spinned off as a separate company. DBSync provides data integration as a SAAS-based, Standalone or hosted integration at a competitive price with a plethora of benefits for business users. Our mission is to provide a strong foundation for businesses in solving complex problems and automating their workflows while acting as a pillar of support for all their data integrations needs. At DBSync we encourage innovation and creativity and our team is diverse comprising of a nice mix of cultural blends. We are a family where each talent is recognised and honed for the best of the individual and the company as a whole. We maintain a very professional, learn and excel vision with a hint of a start-up-like environment making each individual feel important and responsible with an equal opportunity to grow to the sky’s limit! If you have a spirit of enthusiasm to grow beyond horizons, a determination to work hard, confidence to achieve success and influence future visions and products and be a successful part of the next gen trend, DBSync is the place for you! Our Value System 1. We genuinely care 2. We do not waste time on manual or mundane task 3. We have a fun environment 4. We own it 5. We are experts on what we do 6. We win together DBSync has been: We have been rated 4.7 / 5 on G2. We have got around 125 reviews in 2023. Based on the reviews G2 has awarded DBSync following badges. Best Relationship– Winter 2024 Leader Americas Winter 2024 Best Results – Winter 2024 Best Usability – Winter 2024 About the Role: As a Product Marketer for DBSync, you will play a pivotal role in crafting and executing marketing strategies to drive the acquisition, adoption and success of our software products. This role requires a good understanding of data operations and management practices, and familiarity with SaaS apps, databases and data clouds. You will be responsible for creating compelling messaging and campaigns that resonate with our target audience of technical professionals. Job Responsibilities: Craft and deliver product messaging focused on data replication and Change Data Capture (CDC) solutions through various channels, including webinars, videos, and educational content. Comfortably present and host webinars and videos to educate customers on our product capabilities and benefits. Analyze market trends, customer behavior, and competitor offerings to inform marketing strategies. Collaborate with cross-functional teams to create go-to-market plans for new product launches, feature updates, and demand generation. Define target customer segments, value propositions, and distribution channels. Create a wide range of marketing collateral, including product demos, data sheets, whitepapers, blog posts, and videos. Develop presentations, and training materials to empower the sales team with product knowledge and value propositions. Plan and execute marketing campaigns that generate leads and drive customer engagement. Use data and analytics to track campaign performance, ROI, and other relevant metrics. Support account-based marketing (ABM) initiatives and foster growth through customer advocacy. Skills and Qualifications: Bachelor’s degree in computer science, engineering, or related field; MBA with specialization Overall professional experience: 3–5 years, with a strong preference for backgrounds in Strategy, Marketing, or Technology. Min. 2-3 years of experience working in SaaS companies Good technical acumen with good communication skills General understanding of SaaS apps, cloud platforms (Snowflake, Azure, AWS, Redshift), and databases (MySQL, SQL Server, PostGreSQL) Experience working with Salesforce and D365+ is good to have Prior experience in technology consulting or enterprise technology marketing is highly desirable. Exceptional written and verbal communication skills, with the ability to distill technical concepts into clear and engaging messaging. Strong technical aptitude and understanding of DataOps, data management practices, databases, and data clouds. Experience in hosting webinars, creating videos, and delivering technical presentations. Proficiency in marketing tools, analytics platforms, and CRM systems. Strong project management skills and ability to collaborate across cross-functional teams. Job Location: Eastern Europe (Remote) Work Shift: U.S Shift (8:00 AM CST to 5:00 PM CST)