Philippines onlyAbout the RoleAs a Senior Data Warehouse Engineer, where you’ll architect and maintain a highly flexible, enterprise-scale data warehouse that accelerates insights and minimizes redundant work. Leveraging deep expertise in data modeling, governance and Big Data technologies (Hadoop, Spark, Hive, etc.), you’ll design end-to-end ETL pipelines, optimize performance, and build metadata and quality monitoring frameworks. You’ll collaborate closely across business and technical teams, mentor peers, and continuously evolve our data platform to meet the demands of petabyte-scale environments.
Responsibilities
- Architect and implement a flexible, scalable data warehouse aligned with company specifications and business requirements, accelerating delivery and reducing redundant development.
- Design, develop, test, deploy and monitor data models and ETL jobs; rapidly troubleshoot complex issues and optimize calculation logic and pipeline performance.
- Lead data governance initiatives by building and maintaining metadata management and data quality monitoring systems.
- Foster technical team growth through mentorship, knowledge sharing and continuous improvement of collective skills.
Requirements
- 5+ years of hands-on experience designing and developing data lakes and data warehouse solutions.
- Deep expertise in data warehouse modeling and governance, including dimensional modeling, information factory (data vault) methodologies and “one data” principles.
- Proficiency in at least one of Java, Scala or Python, plus strong Hive & Spark SQL programming skills.
- Practical experience with OLAP engines (e.g., Apache Kylin, Impala, Presto, Druid).
- Proven track record in building high-throughput batch pipelines on Big Data platforms.
- Familiarity with core Big Data technologies (Hadoop, Hive, Spark, Delta Lake, Hudi, Presto, HBase, Kafka, Zookeeper, Airflow, Elasticsearch, Redis).
- AWS Big Data service experience is a plus.
- Strong analytical and system-design capabilities, with a clear understanding of business requirements and ability to abstract and architect solutions.
- Collaborative mindset, skilled at building partnerships across teams and stakeholders.
- Preferred: Experience managing petabyte-scale data in Internet-scale environments and resolving critical production incidents.
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