Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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У роли понятный фокус на data-платформе, подробно описан современный стек и указаны сильные льготы, но iGaming связан с азартными играми и подходит не всем.
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Азартный сегментСовременный стекХорошие льготыПонятный круг задач
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Data Engineer (iGaming): Building and scaling data infrastructure for real-time analytics and decision systems with an accent on ingestion pipelines, semantic modeling, and data governance. Focus on distributed processing, streaming integrations, data quality automation, access control, and high-performance platform operations.
Location: Remote, Europe
Company
hirify.global_TECH builds B2B iGaming platforms for operators, providing integrations, consulting, operational support, and scalable technology for millions of active players.
What you will do
Design scalable data transformation layers, production-grade data marts, and semantic models with consistent metrics.
Build and maintain end-to-end ingestion pipelines for internal services, third-party event streams, Kafka, Kinesis, and external APIs.
Automate data quality testing, schema validation, pipeline observability, and protection against silent schema drift.
Optimize queries and pipeline performance through indexing, partitioning, storage formats, and job scheduling.
Build REST APIs and enforce RBAC, row-level security, and column-level masking across data layers.
Automate CI/CD workflows and deployments while collaborating with product managers, engineers, and analysts on technical requirements and architecture.
Requirements
3+ years of production experience in Data Engineering, Software Engineering, or related distributed data systems.
Strong hands-on SQL and database expertise with PostgreSQL and analytical or columnar warehouses such as ClickHouse, BigQuery, or Redshift.
Practical experience orchestrating distributed jobs with Spark, Trino, or Flink and handling event streaming engines such as Kafka, RabbitMQ, or Kinesis.
Proficiency in clean, modular Python for data applications, pipeline orchestration, and REST APIs.
Comfort with Linux, Dockerfiles, Git, and CI/CD pipelines using GitLab CI or GitHub Actions.
Direct experience implementing automated data testing, schema validation, and pipeline observability.
Nice to have
Infrastructure as Code experience with Terraform and exposure to AWS cloud services.
Experience with metadata management tools such as DataHub or OpenMetadata.
Understanding of distributed-systems resilience patterns, including circuit breakers, rate limiting, and connection pooling.
Degree in Computer Science, Software Engineering, or equivalent practical experience.
Culture & Benefits
Remote-first work with technical support and coworking compensation.
Annual benefits budget for sports, medical care, mental health, home office, and language learning.
Paid maternity and paternity leave, monthly childcare allowance, 20+ vacation days, unlimited sick leave, and emergency time off.
Online, offline, and offsite team events plus internal courses and growth programs.
Culture centered on trust, ownership, open feedback, experimentation, resilience, and continuous growth.
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