jobs in Cognizant

全职 AWS Data Engineer 工作, 薪水, Cognizant 公司招聘中 - Ricebowl

Undisclosed

Singapore

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工作地点

  • Singapore

职位描述

岗位职责

Key Responsibilities

  • Design, build, and maintain scalable data pipelines, ETL/ELT workflows, and data integration processes.
  • Develop and optimize SQL queries, data models, and data structures for analytics and operational use cases.
  • Work with diverse data storage systems, including relational, NoSQL, and distributed file systems.
  • Implement data processing solutions using distributed computing frameworks such as Apache Spark or Hadoop.
  • Collaborate with cross‑functional teams to deliver cloud‑native data engineering solutions on AWS or Azure.
  • Develop automated workflows using orchestration tools such as Apache Airflow or Azure Data Factory.
  • Apply DevOps practices including CI/CD automation, IaC, and containerization.
  • Contribute to the design of resilient, scalable, and secure data architecture.

Requirements

  • Experience: Minimum 3 years of professional experience in data engineering, including at least 2 years working with cloud‑native data services.
  • Programming: Proficiency in at least one programming language such as Python, Java, or .NET.
  • Data Fundamentals:
  • Strong SQL expertise in relational databases and data warehouses.
  • Solid understanding of data modeling, data structures, and access patterns.
  • Hands‑on experience with relational databases (e.g., PostgreSQL, MySQL), NoSQL systems (e.g., DynamoDB, CosmosDB), and distributed storage.
  • Cloud Platforms: Practical experience with major cloud services (AWS or Azure), such as:
  • AWS: S3, RDS/Aurora, EMR, Glue, Athena, Redshift, Lambda
  • Azure: Data Lake Storage, Azure SQL, CosmosDB, Data Factory, Synapse
  • Data Processing: Experience using frameworks like PySpark, Apache Spark, Hadoop, and libraries such as Pandas.
  • Orchestration: Familiarity with Airflow, Azure Data Factory, or similar tools.
  • DevOps & Governance:
  • Experience with CI/CD pipeline development.
  • Knowledge of IaC tools such as Git, Docker, and Terraform.
  • Understanding of system design principles for data platforms.

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