Data Engineering Architect

2 weeks ago


Singapore Prudential plc Full time
Data Engineering Architect

Prudential's purpose is to be partners for every life and protectors for every future.

Our purpose encourages everything we do by creating a culture in which diversity is celebrated and inclusion assured, for our people, customers, and partners.

We provide a platform for our people to do their best work and make an impact to the business, and we support our people's career ambitions.

We pledge to make Prudential a place where you can Connect, Grow, and Succeed.


The Data Engineering Architect, will be responsible for designing, implementing, and optimizing scalable data solutions for the Finance for Future Programme for Finance Data Repository (FDR).

The position will involve working closely with the IT Delivery Lead and Data Solution Architect on a day-to-day basis.

You will also require to engage with business stakeholders to understand business requirements and translate them into robust data architectures.

You will lead the design and development of data pipelines, ensuring efficient extraction, transformation, loading of data from various sources and data distribution to any downstream reporting needs.

Role and Responsibilities

  • Design, develop and deliver the building of data pipelines across various integration points for the global FDR
  • Develop, confirm pipeline tools for ingestion, transformation, and distribution, based on fact finding and assessment of existing solutions within Prudential frameworks
  • Implement data models, ensuring scalability, performance, and reliability
  • Collaborate with crossfunctional teams to understand data requirements and provide technical advice
  • Select appropriate tools and technologies for data storage, processing, and analysis
  • Optimize data infrastructure for costeffectiveness and performance working with Develops team to
  • Ensure data security, compliance, and governance standards are met
  • Indepth knowledge of the principles and practices of good systems design

Qualifications

  • Experience Level: Proven experience in delivering enterprise data platform projects
  • Education Level: Bachelor's degree in a relevant field; advanced degree preferred
  • Personal Attributes: Strong analytical skills, leadership capabilities, effective communication, and problemsolving ability
  • Specific Skills: Deep technical knowledge in data engineering, database management and data warehousing technologies. (e.g. SQL, Python, Spark, Azure stack, Databricks)
  • Strong understanding of distributed computing frameworks like Hadoop, Spark, or Flink.
  • Knowledge of database technologies like SQL databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra)
  • Familiarity with data integration tools, data pipeline orchestration tools, and workflow management systems

Mandatory skills

  • Strong background in data engineering, with experience architecting complex data systems in largescale environments
  • Experience in successful delivery of complex data related projects end to end.
  • Experience in Agile and DevSecOps delivery, quality practices, techniques and tools required for all aspect of data engineering/ data platforms
  • Experience with cloudbased technologies incl. Microsoft Azure, Google Cloud, API, inclusion of streaming data, business intelligence tools, Oracle cloud integration
  • Experience with JIRA, Confluence, Github, Bitbucket and other similar developer tools

Preferred skills

  • Experience in data visualization and analytics, supporting a dataenabled organization.
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