Data Engineer Real-Time Pipelines & Scalable Platforms

TALENTSIS PTE. LTD.

Singapore

On-site

SGD 90,000 - 140,000

Full time

47 hours ago
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Job summary

TALENTSIS PTE. LTD. is seeking Data Engineers to design, develop, and maintain scalable data platforms for efficient data collection, storage, processing, and analytics.

The role involves building robust batch and real-time data pipelines and ensuring data quality, governance, and availability to support BI and advanced analytics initiatives. You will collaborate with stakeholders, data scientists, and analytics teams to implement data models and pipelines, while ensuring security and compliance

Qualifications

  • 3+ years of experience designing, building, and optimising data pipelines and architectures.
  • Experience with ETL tools such as Informatica or Talend.
  • Proficiency in SQL, Python, and DBMS.
  • Experience with big data technologies such as Spark, Hadoop, and Hive.
  • Knowledge of data security, governance, and quality practices.

Responsibilities

  • Collaborate with customers and stakeholders to understand data requirements and provide technical solutions.
  • Partner with data scientists to support data modelling and analytics initiatives.
  • Design, develop, and maintain scalable data models, ETL/ELT processes, data warehouses, and pipelines for large data volumes.
  • Build and optimise batch, near real-time, and real-time data processing solutions.
  • Monitor and improve performance, reliability, and scalability of data platforms.

Skills

SQL
Python
DBMS
Data Wrangling
Data Visualisation
ETL/Data Integration

Tools

Informatica
Talend
Spark
Hadoop
Hive

Job description

TALENTSIS PTE. LTD. is seeking Data Engineers to design, develop, and maintain scalable data platforms for efficient data collection, storage, processing, and analytics.

The role involves building robust batch and real-time data pipelines and ensuring data quality, governance, and availability to support BI and advanced analytics initiatives. You will collaborate with stakeholders, data scientists, and analytics teams to implement data models and pipelines, while ensuring security and compliance

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