Job description for Lead Data Platform at PT Tricada Intronik
RESPONSIBILITIES
- Lead, mentor, and provide technical guidance to a stream-aligned Data Platform team spanning Data Engineering and Applied Intelligence capabilities, fostering engineering excellence and collaboration.
- Oversee the implementation and governance of data processing, data quality, metadata, and intelligence capabilities within the product domain.
- Design and guide scalable data pipelines, processing workflows, and reusable data capabilities aligned with platform architecture and engineering standards.
- Establish and enforce engineering standards for code quality, peer reviews, documentation, and QA processes to ensure reliable and maintainable data capabilities.
- Drive the creation and management of reusable data artifacts, including metadata, lineage, catalog, and documentation within the company’s data platform ecosystem.
- Collaborate with cross-functional engineering teams to ensure data services and processing capabilities are properly integrated into product delivery and platform workflows.
- Collaborate with product owners and business stakeholders to translate business needs into technical requirements and data-driven solutions.
- Sync weekly with the Shared Services Pool to share learnings, discuss roadmaps, and contribute to the evolution of our central data platforms and patterns (e.g., Kafka, Airflow, ClickHouse, OpenMetadata).
- Hands-on experience with Java and Spring Boot, particularly for integrating data services into platform applications.
- Experience working with modern data platform ecosystems, including streaming, orchestration, and analytical platforms.
- Exposure to advanced data analytics, machine learning, or AI capabilities, including model integration or intelligent data processing use cases.
- Experience working in cloud environments (GCP, AWS, or Azure).
- Knowledge of the telecommunications (Telco) domain and operational data environments.
REQUIREMENTS
- 3–5 years of hands-on experience in data engineering, data platform implementation, or scalable data processing environments.
- Proven experience in a leadership or mentorship role, with a track record of guiding technical teams in delivering data-related capabilities.
- Strong proficiency in Python and SQL for data processing, pipeline development, and data platform implementation. Hands-on experience with modern data platform technologies, such as workflow orchestration (e.g., Airflow), event streaming (e.g., Kafka), and analytical or distributed databases (e.g., ClickHouse).
- Good understanding of data processing lifecycle, metadata management, data quality, and governance-support capabilities.
- Hands-on experience in metadata management, data discovery, lineage, or governance-support capabilities using platforms such as OpenMetadata or similar data catalog/governance tools.
- Solid software engineering fundamentals, including version control (Git), CI/CD, documentation, and testing practices.
- Strong collaboration and communication skills in working with cross-functional engineering and product teams.
