Data Engineer
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Summary
A data engineering role in Singapore centered on large-scale analytical data platforms: building and optimizing workloads on Apache Doris and Trino, working with lakehouse table formats like Apache Iceberg, and reading/migrating Snowflake and Spark workloads. Day to day involves deep SQL tuning, distributed MPP query troubleshooting, and pipeline automation in Python, Java, or Scala.
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.