Data Engineering Manager leading data engineers at Intrepid Asia for Ecommerce and Digital Solutions. Overseeing data pipelines, architecture, and governance while driving innovation and efficiency.
Responsibilities
Lead, manage, and mentor a team of data engineers, fostering their professional growth and cultivating a collaborative, high-performance culture
Oversee the end-to-end data lifecycle, ensuring the robustness and performance of our data pipelines orchestrated with Apache Airflow and transformations managed by dbt
Manage and optimize our dual data warehouse strategy, leveraging StarRocks for transformation and analytics, and Google BigQuery for large-scale data warehousing
Champion DataOps principles, implementing best practices for CI/CD, automated testing, and infrastructure as code
Design and implement a comprehensive data quality framework, establishing metrics and SLAs for our critical datasets
Implement and manage a data observability platform to proactively monitor, alert, and troubleshoot issues across the data stack, minimizing data downtime
Develop and own our data governance strategy to ensure data accuracy, security, and compliance
Design and evolve our data architecture to be future-ready for enterprise-grade data services and new business initiatives
Collaborate closely with data scientists, analysts, product managers, and business stakeholders to understand data requirements and deliver impactful solutions
Drive cost-optimization initiatives across our data stack, ensuring we achieve maximum value from our cloud and technology investments
Requirements
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field
8+ years of hands-on experience in data engineering, with a proven track record of building and maintaining large-scale data pipelines
3+ years of experience in a leadership or management role
Expert proficiency in SQL and Python
Exposure to building data infrastructure to support AI/ML workflows (e.g., feature stores, MLOps)
Deep, hands-on experience with modern data stack tools, including: Workflow Orchestration: Apache Airflow; Data Transformation: dbt; Cloud Data Warehouses: Google BigQuery and/or familiarity with other similar Data Warehouse technologies i.e. Snowflake, Azure Synapse Analytics, Databricks; Modern OLAP Databases: StarRocks or similar (e.g., ClickHouse, Druid)
Familiarity with OLTP databases like MySQL and Postgres is required
Solid understanding of DataOps principles, data modelling, ETL/ELT design patterns, and data architecture
Proven experience working in an Agile/Scrum development environment
Benefits
Competitive compensation
Generous benefits including comprehensive insurance
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