- Singapore
Working Location
Job Description
Responsibilities
Job Description:
Role: Big Data Engineer (PySpark & Scala)
Location: Singapore
Experience: 6 – 12 Years
Big Data Engineer (PySpark & Scala)
Role Summary
We are seeking a highly skilled Big Data Engineer with strong experience in PySpark and Scala to design, build, and optimize large-scale data processing systems. The candidate will work on distributed data platforms, enabling real-time and batch analytics solutions across enterprise data ecosystems.
The role involves building scalable data pipelines, data lakes, and streaming solutions leveraging modern big data technologies.
Key Responsibilities
Data Engineering & Development
Design and develop scalable data pipelines using PySpark and Scala
Data Platform & Architecture
Data Processing & Optimization
Streaming & Real-Time Data
Cloud & Modern Data Stack
Data Quality & Governance
Collaboration & Delivery
Big Data Ecosystem
Hadoop: HDFS, Hive, YARN
Data ingestion tools: Kafka, Sqoop
Data formats: Parquet, ORC, JSON, Avro
Programming & Query
Python / Scala
Advanced SQL (joins, aggregations, optimization)
Shell scripting / Unix basics
Streaming & Messaging
Kafka (must-have)
Event-driven architecture
Real-time data processing frameworks
DevOps & Tools
Git, CI/CD pipelines
Docker / Kubernetes (good to have)
Scheduling tools (Airflow / Control-M)
Cloud (One or more preferred)
AWS / Azure / GCP
Databricks / Snowflake exposure
Domain Experience (Preferred)
BFSI / Banking / Payments domain
Experience working with high-volume financial datasets
Knowledge of data compliance and regulatory reporting
This role requires a combination of:
Strong PySpark + Scala coding
Deep big data architecture knowledge
Hands-on experience with streaming + cloud data engineering
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