Data platform engineer for analytics and AI

HBX Group is a leading B2B ecosystem player in the TravelTech space, connecting and empowering businesses in the ever-evolving world of travel. We drive growth for our clients and partners while removing friction from the end-to-end travel experience. Our cloud-based technology platforms offer fast and reliable access to a unique portfolio of travel products & services, while rich data and intelligence seamlessly connect supply and demand worldwide.

• Own end-to-end responsibility for the reliability, performance and scalability of all Data, ML & AI platform, ensuring alignment with business objectives and technology strategy
• Define and drive the technical roadmap and long-term evolution of the platform ecosystem, including data ingestion, transformation, analytics, machine learning and AI enablement capabilities, ensuring alignment with business objectives and technology strategy.
• Act as the ultimate technical authority for the domain establishing technology standards, frameworks and engineering best practices.
• Ensure platform scalability, reliability, security, maintainability and cost-efficiency as business demand grows.
• Evaluate emerging technologies and define adoption strategies that improve productivity, platform capabilities and business outcomes.
• Lead multiple engineering teams through their respective Team Leads, providing strategic direction, technical leadership and operational guidance
• Act as the primary technology partner for senior business stakeholders, Product Directors, Engineering leaders and Executive Leadership
• Foster a culture of engineering excellence, ownership, innovation, accountability and continuous improvement
• Mentor senior engineers and Team Leads, supporting their technical and leadership development
• Assume end-to-end ownership of all Data Platform services, ensuring agreed service levels, platform availability, reliability and performance.
• Establish and monitor service KPIs, SLAs and operational metrics across all platform components

• Exceptional leadership skills with proven ability to lead multiple engineering teams through Team Leads and senior technical contributors.
• Strong stakeholder management capabilities, with experience engaging and influencing Director and C-Level stakeholders.
• Strategic mindset with the ability to align technology investments with business objectives.
• Excellent communication and presentation skills, capable of translating complex technical concepts into business language.
• Strong decision-making and prioritization skills in complex and rapidly changing environments.
• Proven ability to balance operational stability, technical innovation and business delivery.
• Strong people leadership capabilities, including coaching, mentoring and organizational development.
• Demonstrated experience building high-performing engineering organizations and fostering engineering excellence.
• Excellent analytical and problem-solving capabilities.
• Resilience and ability to operate effectively under pressure while managing competing priorities.
• Strong command of English, both written and verbal.
• Deep expertise designing, operating and evolving enterprise-scale Data Platforms supporting Analytics, Machine Learning and AI workloads.
• Strong understanding of modern Data Architecture patterns including Data Warehousing, Lakehouse, Data Mesh and Data Product concepts.
• Strong experience with Snowflake architecture, performance optimization, security and governance.
• Expert knowledge on modern ELT frameworks
• Extensive experience with AWS cloud services and cloud-native data architectures.
• Strong knowledge of data integration patterns including batch, streaming, CDC and event-driven architectures.
• Experience supporting enterprise BI platforms such as Tableau and ensuring data product scalability and performance.
• Understanding of semantic layers, consumption patterns and self-service analytics strategies.
• Solid understanding of machine learning lifecycle requirements, MLOps concepts and AI platform enablement.
• Experience supporting infrastructure and services required for ML and AI workloads in production environments.
• Strong software engineering background with expertise in Python and SQL.
• Experience with CI/CD, Infrastructure as Code, Git-based development workflows and platform automation.
• Deep knowledge of observability, monitoring, alerting and platform reliability engineering practices.
• Experience implementing enterprise-grade access controls, auditing and lineage capabilities.
• Будет плюсом: Experience with OpenMetadata or similar metadata management platforms; Experience with Great Expectations, Soda, Monte Carlo or similar data quality frameworks; Familiarity with GenAI, LLMOps and emerging AI platform technologies; Knowledge of Kubernetes and container orchestration technologies; Experience with FinOps and cloud cost optimization strategies; Experience in retail, e-commerce, tourism or hospitality industries; Experience leading large-scale Data & AI transformation initiatives; Exposure to global and distributed engineering teams

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