Tasks:
- Collaborate with product manager & cross-functional team to determine the product roadmap that aligns with the broader company vision;
- Be responsible for the technical architecture and execution/delivery of projects that meet the business objectives;
- Define and continuously optimize your team's working model (sprint/agile processes) for efficiency & quality;
- Manage & lead the team through critical projects;
- Provide sound judgement on hard tradeoffs between scopes, engineering capacity, and time constraints;
- Set a high bar for engineering talent recruitment;
- Coach, develop, and grow your engineering team to make bigger impacts and job satisfaction;
- Build a strong culture of teamwork, guide team members to resolve conflicts and help build a cohesive relationship.
Desired skills & experience:
- 5+ years of professional software development experience;
- 2+ years of management experience leading software engineers;
- Strong communication, leadership, and problem-solving skills;
- Track record of managing, recruiting, and retaining strong engineering talent and growing effective teams;
- Experience working with multi-functional, globally distributed teams to coordinate work and deliver solutions that span multiple teams;
- Experience working with PMs, designers, data scientists, and infrastructure teams to identify opportunities, prioritize roadmaps, and solve problems;
- Experience with distributed systems, microservices implementation, such as Golang, Java, Scala;
- Strong technical skills with experience in large-scale, distributed systems, including SQL/NoSQL storage, transactional updates, asynchronous processing with message queues like Kafka, logging, system monitoring, and performance tuning;
- Desire knowledge of microservices, distributed systems.
We offer:
- Attractive salary package
- Paid vacation and sick days
- Extended health benefits
- Training and development allowance
Good to have skills:
- Experience or having domain knowledge in online payment, eCommerce, credit card processing, risk management, or fraud detection (big plus);
- Experience with Data Analysis and Data Processing using big data technologies: ELK stack (Elasticsearch, Kibana), DataLake, Spark, Hadoop;
- Skilled in Data Science or Machine Learning.
