GTM Engineering Manager managing Salesforce Developers and CPQ Specialists for GTM technology initiatives. Driving execution and collaborating with global teams to deliver on strategic roadmaps.
About the role
- 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
- Ample leave
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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