Senior Data Engineer

r systems (singapore) pte limited; Singapore; On-site; SGD 150,000 - 190,000; Full time

Job summary

r systems (singapore) pte limited is seeking an experienced Data Engineer to implement enterprise Lakehouse platforms and data products. You will build scalable batch/streaming pipelines and enable content extraction across formats, including images, videos, and audio transcripts.

You will work with open table formats like Iceberg/Delta Lake, support GenAI/data pipelines, and ensure data quality with contracts and SLAs. Strong Spark/PySpark/SQL/Python/Scala and Java proficiency is required.

Qualifications

• 8-12 years of experience in Data Engineering, Big Data, Data Lake, or Lakehouse implementations.
• Hands-on experience with Databricks, Snowflake, Cloudera, Azure, AWS, GCP, Huawei, or Alibaba data platforms.
• Hands-on experience in developing Data products and Market place.
• Strong expertise in Spark, PySpark, SQL, Python and Scala.
• Strong programming skills (Java, Scala, Python, SQL).
• Experience with Iceberg, Hudi, Delta Lake and object storage platforms.
• Experience implementing data ingestion, transformation, reconciliation and data quality frameworks.
• Experience with Trino, Dremio, Hive, Impala, Kafka, Flink, Spark Streaming and Airflow.

Responsibilities

• Implement and operationalize enterprise Lakehouse platforms, data products, and data marketplace capabilities.
• Develop scalable batch, streaming, CDC, and API-based data ingestion pipelines.
• Develop scalable multimodal data ingestion pipelines including content extraction from various file formats, regex for specific field extraction, content extraction from embedded images, frame extraction from video files, transcript extraction from audio files, etc.
• Build, test, and maintain foundation and business data products with agreed data contracts, SLAs, and data quality controls.
• Implement open table formats such as Iceberg, Hudi, and Delta Lake.
• Support RAG, vector search, GenAI and agentic data pipelines.
• Perform performance tuning, optimization, production support, and root cause analysis.
• Create technical documentation, deployment guides, and operational runbooks.
• Ensure compliance with engineering standards, DevSecOps controls, and software delivery practices.

Skills

Data engineering

Spark

PySpark

SQL

Python

Scala

Java

Tools

Databricks

Snowflake

Cloudera

Azure

AWS

GCP

Iceberg

Hudi

Delta Lake

Trino

Dremio

Hive

Impala

Kafka

Flink

Spark Streaming

Airflow

Job description

Responsibilities:

• Implement and operationalize enterprise Lakehouse platforms, data products, and data marketplace capabilities.
• Develop scalable batch, streaming, CDC, and API-based data ingestion pipelines.
• Develop scalable multimodal data ingestion pipelines including content extraction from various file formats, regex for specific field extraction, content extraction from embedded images, frame extraction from video files, transcript extraction from audio files, etc.
• Build, test, and maintain foundation and business data products with agreed data contracts, SLAs, and data quality controls.
• Implement open table formats such as Iceberg, Hudi, and Delta Lake.
• Support RAG, vector search, GenAI and agentic data pipelines.
• Perform performance tuning, optimization, production support, and root cause analysis.
• Create technical documentation, deployment guides, and operational runbooks.
• Ensure compliance with engineering standards, DevSecOps controls, and software delivery practices.

Requirement:

• 8-12 years of experience in Data Engineering, Big Data, Data Lake, or Lakehouse implementations.
• Hands-on experience with Databricks, Snowflake, Cloudera, Azure, AWS, GCP, Huawei, or Alibaba data platforms.
• Hands-on experience in developing Data products and Market place.
• Strong expertise in Spark, PySpark, SQL, Python and Scala.
• Strong programing skills (Java, Scala, Python, SQL).
• Experience with Iceberg, Hudi, Delta Lake and object storage platforms.
• Experience implementing data ingestion, transformation, reconciliation and data quality frameworks.
• Experience with Trino, Dremio, Hive, Impala, Kafka, Flink, Spark Streaming and Airflow.