راهبر تیم مهندسی داده

Job Description

Wallex is a FinTech company providing a secure cryptocurrency exchange platform and digital asset payment solutions.
With a vision to become a leading global FinTech enterprise, Wallex is recognized as one of the largest cryptocurrency exchange platforms in Iran, supporting the online trading of over 130 cryptocurrencies.
We are seeking an experienced and inspiring Data Engineering Lead to lead our growing Data Engineering team and shape the strategic direction, development, and operation of our data platform.
In this role, you will be responsible for scaling our data infrastructure across data warehousing, real time processing, and large scale analytics. You will lead the team, drive architectural decisions, ensure operational excellence, and enable the organization to access reliable, timely, and high quality data for decision making.

Responsibilities:
•Lead, mentor, and develop a high performing team of Data Engineers while promoting collaboration, ownership, innovation, and technical excellence.
•Manage team performance, conduct performance reviews, oversee capacity planning, and support hiring and onboarding activities.
•Define and execute the long term vision and roadmap for the Wallex data platform in alignment with business and technology objectives.
•Lead key architectural decisions across the data ecosystem, ensuring solutions are scalable, reliable, secure, cost effective, and aligned with organizational requirements.
•Oversee the delivery of data engineering initiatives from requirements gathering and solution design to implementation, testing, validation, and deployment.
•Partner closely with Data Science, Analytics, Product, Engineering, and other stakeholders to understand business needs and translate them into effective data solutions.
•Manage and prioritize the Data Engineering backlog based on business value, technical dependencies, urgency, and available capacity.
•Ensure the reliability, security, performance, and observability of the data platform through effective monitoring, alerting, and DataOps practices.
•Establish and enforce standards for data quality, integrity, security, governance, and metadata management across the organization.
•Drive continuous improvement in data engineering practices, development workflows, platform reliability, and operational efficiency.
•Remain hands on when needed, particularly during critical incidents, and contribute directly to pipeline development, troubleshooting, and infrastructure maintenance.

Requirements:
•At least 7 years of hands on experience in Data Engineering, Business Intelligence, or Big Data environments.
•At least 3 years of proven experience in a technical leadership or people management role.
•Deep understanding of data engineering principles, modern data architectures, data warehousing, data lakes, and data modeling.
•Proven experience designing and building complex batch and real time data pipelines.
•Strong knowledge of distributed processing frameworks, large scale data storage technologies, and workflow orchestration tools.
•Strong proficiency in SQL and experience working with analytical databases, including OLAP and columnar databases, as well as transactional OLTP databases.
•Strong programming skills in at least one relevant language, preferably Python.
•Strong understanding of data platform reliability, monitoring, observability, and operational best practices.
•Experience with infrastructure automation, Infrastructure as Code, and continuous integration and continuous delivery practices for data platforms and pipelines.
•Excellent leadership, mentoring, and team development skills.
•Strong project management, planning, and prioritization skills. Experience with Agile or Scrum environments is preferred.
•Excellent communication and stakeholder management skills, with the ability to translate complex technical concepts for both technical and nontechnical audiences.
•Experience with cloud platforms such as AWS, Azure, or GCP is considered an advantage.

We build, not watch. This is where you belong.