Senior Data Engineer – Full Stack

This is a fully remote position, open to applicants in Europe.

📋 Description

• Comprehensive Architecture & Delivery: Define, design, and implement intricate data infrastructure, pipeline ingestion, and transformation layers across various business units (Esports, Festivals, Commerce, HR, Finance, and FACEIT);

• Pipeline & Platform Engineering: Develop scalable architectures adhering to well-architected framework principles (reliability, security, performance, and automation). Oversee workflow orchestration, CI/CD pipelines, and infrastructure automation;

• Data Modeling & Semantic Layers: Standardize enterprise-grade dimensional modeling (Kimball/Inmon), star schemas, and centralized semantic layers to establish reliable, cross-pillar metrics;

• AI-Ready Datasets: Generate clean, optimized, AI-ready datasets with structured metadata, clear naming conventions, and thorough documentation to facilitate downstream AI agents and cognitive models;

• Technical Standards & Governance: Set and uphold best practices for Python/SQL development, dbt optimization, testing frameworks, and version control throughout the hybrid data domain;

• Efficiency & Cost Optimization: Actively monitor and enhance performance and infrastructure platform costs related to storage, compute, and query layout (e.g., BigQuery configurations);

• Stakeholder Partnership: Serve as a strategic collaborator to business leaders and analysts, translating complex goals into scalable self-service data products;

• Incident Response & Data Integrity: Lead incident response initiatives for system downtimes and data quality issues, implementing automated testing to ensure adherence to Industry Standard Data Integrity;

• Mentorship & Growth: Guide junior and mid-level engineers through thorough code reviews and technical advice, fostering their professional development and elevating team standards.

⛳️ Requirements

• Expert Technical Skills: Proficiency in SQL and advanced Python/programming languages for high-performance data processing;

• Modern Data Stack (MDS) Expertise: Extensive, hands-on experience with cloud data warehouses (e.g., BigQuery internals), workflow orchestration platforms, and dbt optimization at scale (macros, package management);

• Data Architecture & Infra: Demonstrated history in dimensional modeling, cloud architecture patterns, Identity and Access Management (IAM), networking, and Infrastructure as Code (IaC);

• AI & Industry Awareness: Significant knowledge of the evolving data ecosystem, combined with practical experience in building AI agents and effectively prompting AI;

• Project Leadership: Proven ability to lead end-to-end projects, mitigate risks during deployment cycles, and manage cross-functional technical delivery;

• Communication Excellence: Exceptional technical storytelling abilities; capable of balancing intricate technical details with strategic business context for both engineering teams and non-technical stakeholders;

• Collaboration & Soft Skills: Technical leadership, strategic thinking, ownership mentality, attention to detail, and a strong enthusiasm for promoting self-service and data quality.

🏝️ Benefits

• Health insurance

• 401(k) matching

• Flexible working hours

• Paid time off