# Data Architect

**Company:** [Infosys Singapore & Australia](http://jobs.workable.com/companies/wC83hmrGHu1htzj3qou2pH.md)
**Location:** Singapore, Singapore
**Workplace:** on site
**Employment type:** Full-time
**Department:** AIX-AI & ML

[Apply for this job](http://jobs.workable.com/view/63baea4f-aede-4aa5-9934-624019309f6a)

## Description

We are looking for a highly experienced and skilled Data Architect to join our team. The ideal candidate will have 12-15 years of experience in architecting solutions of data engineering, focusing on ELT and PySpark/Hadoop workloads. In addition to strong solution and delivery skills, the ideal candidate will also have a view on business growth and managing stakeholders.

Responsibilities:

-   Design and implement high-performance, scalable, and secure data architectures.
-   Work with business stakeholders to understand their data needs and translate them into technical requirements.
-   Design and develop data pipelines and workflows using ELT principles and PySpark/Hadoop
-   Optimize data pipelines and workflows for performance and efficiency
-   Work with data scientists and engineers to ensure that data is accessible and usable for analytics and machine learning
-   Implement data governance and security best practices
-   Manage and mentor data engineers
-   Contribute to the overall data engineering strategy and roadmap

## Requirements

Qualifications:

-   12-15 years of experience in data engineering, with a focus on ELT and PySpark/Hadoop workloads
-   Strong experience in designing and implementing high-performance, scalable, and secure data architectures.
-   Experience with data governance and security best practices
-   Experience in managing and mentoring data engineers
-   Excellent communication and interpersonal skills
-   Ability to work independently and as part of a team
-   Strong problem-solving and analytical skills

Desired Skills:

-   Experience with cloud computing platforms such as AWS, Azure, or GCP
-   Experience with big data technologies such as Spark, Hadoop, Hive, and Kafka
-   Experience with data warehousing and data lakes
-   Experience with DevOps and MLOps practices

-   Experience with data science and machine learning, streaming data processing
-   Experience with real-time analytics, data visualization and reporting tools