Senior Engineering Manager (On-site)

Job summary

This role involves leading and mentoring two engineering teams focused on clustering infrastructure and exposure data systems, critical to the company's operations in the blockchain analytics sector. The position requires driving the technical vision and roadmap while ensuring system reliability and scalability.

Qualifications

• Strong hands-on software and data engineering skills, including code review and architectural decision-making.
• Extensive experience with large-scale data processing and distributed systems (e.g., Spark, Flink, Databricks).
• Proven track record of leading high-performing engineering teams while remaining technically engaged.
• Interest in fostering an AI-first environment within the teams.
• Ability to manage multiple problem domains and switch between strategic planning and hands-on contributions.
• Collaborative leadership style with a focus on technical credibility.
• Passion for tackling large-scale graph, clustering, and real-time data tracing challenges.
• Commitment to system reliability and cost-effective engineering practices.
• Interest in blockchain and cryptocurrencies, with a willingness to learn.

Responsibilities

• Build and mentor high-performing engineering teams in clustering and exposure.
• Drive the technical vision and roadmap, balancing various operational factors.
• Oversee the re-architecture of exposure systems for real-time fund tracing.
• Develop the next-generation clustering platform to adapt to the evolving blockchain landscape.
• Collaborate with data producers and product stakeholders to enhance developer and data science experiences.
• Establish engineering processes and best practices to improve team efficiency.
• Engage in hands-on problem-solving when necessary, including architecture and incident response.
• Promote a culture of quality and continuous improvement in data systems.

Skills

• Proficiency in AWS serverless architectures, Kubernetes, Spark, Flink, Java, Python, Databricks, and Terraform.
• Familiarity with data formats like Parquet, Iceberg, Delta, and Paimon.

Education

• Relevant degree in Computer Science, Engineering, or a related field is preferred but not explicitly stated.

Tools

• AWS, Kubernetes, Spark, Flink, Java, Python, Databricks, Terraform, GitHub.