Data Architect
At a glance
Mid-level Data Architecture & Governance role at Infosys Singapore & Australia. Singapore · full-time.
Pay not stated Data Architect salary
dataroles summary, based on the employer's posting.
What you'll do
- Build secure, scalable data architectures and create ELT pipelines and workflows with PySpark and Hadoop
- Tune data workflows to improve their speed and efficiency
- Turn business data needs into technical plans, then make datasets usable for analytics and machine learning
- Apply governance and security practices, and guide data engineers through mentoring
- Help set the direction and roadmap for data engineering work
What you bring
- Twelve to fifteen years in data engineering, focused on ELT and PySpark or Hadoop workloads
- A strong record of designing and delivering secure, scalable data architectures
- Experience applying data governance and security practices and mentoring data engineers
Who this fits
This role suits a senior data architect who can work with business stakeholders and lead delivery while contributing to data engineering direction. The position is onsite in Singapore.
From the employer
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
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