Data Engineer - Apache Doris
Posted Updated 1
view
Summary
Contract data engineering role (12+ months, extendable) in Singapore focused on building and optimizing analytical workloads on Apache Doris, with Trino, Iceberg lakehouse tables, Snowflake/Spark migration support, and CI/CD-managed data pipelines.
Position: Data Engineer - Apche Doris
Location: Singapore
Contract: 12+ Months and Extendable
• Hands-on production experience with Apache Doris (or a comparable MPP OLAP engine - StarRocks, ClickHouse, Greenplum). • Strong, deep SQL expertise - complex analytical queries, window functions, CTEs, query optimization. • Solid understanding of Doris architecture (FE/BE), the three data models (Duplicate/Aggregate/Unique), partitioning, bucketing, and tablet/replica management. • Experience with Apache Iceberg (or comparable open table formats - Delta Lake, Hudi) and lakehouse / external-catalog federation. • Practical experience with Snowflake and/or Apache Spark- enough to read, understand, and migrate existing workloads. • Understanding of distributed / MPP query execution: join distribution, runtime filters, memory management, and data skew. • Hands-on production experience with Trino (or PrestoSQL/Presto) • Understanding of distributed query execution: MPP architecture, join distribution, memory/spill behaviour, partition pruning, and predicate pushdown • Experience with cloud object storage and columnar file formats (Parquet, ORC) • Proficiency in at least one programming language (Python, Java, or Scala) for tooling, UDFs, and Automation • Version control (Git) and CI/CD for data pipelines.
• Hands-on production experience with Apache Doris (or a comparable MPP OLAP engine - StarRocks, ClickHouse, Greenplum). • Strong, deep SQL expertise - complex analytical queries, window functions, CTEs, query optimization. • Solid understanding of Doris architecture (FE/BE), the three data models (Duplicate/Aggregate/Unique), partitioning, bucketing, and tablet/replica management. • Experience with Apache Iceberg (or comparable open table formats - Delta Lake, Hudi) and lakehouse / external-catalog federation. • Practical experience with Snowflake and/or Apache Spark- enough to read, understand, and migrate existing workloads. • Understanding of distributed / MPP query execution: join distribution, runtime filters, memory management, and data skew. • Hands-on production experience with Trino (or PrestoSQL/Presto) • Understanding of distributed query execution: MPP architecture, join distribution, memory/spill behaviour, partition pruning, and predicate pushdown • Experience with cloud object storage and columnar file formats (Parquet, ORC) • Proficiency in at least one programming language (Python, Java, or Scala) for tooling, UDFs, and Automation • Version control (Git) and CI/CD for data pipelines.