dourolabs.xyz - Data Systems Operations Lead
Requirements
• 5+ years in technical Engineering operations, data systems engineering, or technical project management for distributed systems • Proven track record running mission-critical systems; experienced with incident management and on-call operations • Deep understanding of data systems and distributed infrastructure • Experience with financial markets, market data, or real-time systems • Background at tier-1 financial institutions (exchanges, prime brokers), crypto exchanges or infrastructures. • Able to communicate complex technical concepts to both engineers and C-suite executives • Cryptocurrency or blockchain infrastructure operations experience • DevOps, SRE, or infrastructure engineering at scale • Market data systems or oracle infrastructure background • Security or risk management experience • Success migrating institutional workflows to new systems • Relationships with exchanges, market makers, or trading desks • You're a problem-solver who owns complex challenges from zero to one. You've earned trust in previous roles, which is why people listen to your solutions. You understand that operations serve customers and users - you're driven by reliability that matters, not perfection for its own sake. You're technically deep enough to debug distributed systems, but mature enough to know that systems design beats heroic firefighting. • That sounds like you?
Responsibilities
• Own Pyth Lazer Operations & Service Management • Own all runtime requirements for Pyth Pro: monitoring, provisioning, risk metrics, and SLA management • Establish service targets for each iteration and measure improvements and risk reduction • Express detailed requirements that enable automation of feed provisioning and feed reviews • Ensure all feeds meet quality standards and institutional requirements • Investigate and Lead Automation Implementation • Investigate and lead implementation of automation opportunities around price feeds • Identify repetitive operational tasks and opportunities for systematic automation to reduce toil and human error • Proactively identify system vulnerabilities and risks; propose and champion solutions • Think strategically - anticipate failure modes and design for resilience • Lead Incident Response & Data Forensics • When incidents occur, lead data forensics and quantify user impact • Work on fixes that measurably reduce recurrence and drive both tactical and strategic solutions • Make high-stakes decisions during incidents • Own the requirements and success metrics for incident prevention • Bridge Technical & Business Operations • Manage relationships with institutional users and data providers; ensure their needs are understood • Advocate internally for operational improvements • Prioritize user satisfaction and think in terms of identifying and solving problems • Balance hands-on execution with strategic thinking about long-term improvements
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