Lead Data Platform

Deskripsi pekerjaan Lead Data Platform 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.