MABASA / LINKEDIN
Data Engineer-Spark/Iceberg + SQL
Ampstek
- Location
- Singapore, Singapore
- Work type
- contract
- Source publication date
- Original publication date not confirmed
- Source closing date
- Not supplied — check original advert
Job description from the source
Job Title: **Data Engineer \- Apache Doris** Data Engineer \- • 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. **Mandatory skills\*** **Apache Doris / Spark/Iceberg \+ SQL** **Desired skills\*** Apache Iceberg / Lakehouse technologies, Advanced SQL, Trino/Presto, Snowflake, Spark
Check the original advert before applying
Apply through the employer or original publisher. An external site may require registration. Opening an advert does not submit an application.
Content is supplied by an external publisher and may change. For source and availability limits, read our listing disclaimer. How to check an original listing ↗