DUTIES AND RESPONSIBILITIES

HCLTech partners with ANZ Bank which is one of the BIG4 Australia-based banks to build engineering teams for cutting-edge digital transformation projects.

Our purpose is to shape a world where people and communities thrive. We are making this happen by improving our customers’ financial wellbeing so they can achieve incredible things – be it buying a home, building a business or saving for things big or small. We are looking for people who are passionate about transformational change and help us redefine banking for the future.

Be a part of building the ideal data ecosystem from scratch. Ensuring the right data is generated from all applications and sourced at the right velocity with the complete depth and breadth to ensure complete coverage and reuse. This is your opportunity to build new, not fix old.

What will your day look like?

• Build and run the data processing pipeline on Google Cloud Platform (GCP) HCL Technologies – Where Values Drive Velocity

• Work with Implementation teams from concept to operations to provide deep technical expertise for successfully deploying large scale data solutions in the enterprise and use modern data/analytics technologies on GCP

• Design pipelines and architectures for data processing

• Implement methods for DevOps automation of all parts of the built data pipelines to deploy from development to production

• Formulate business problems as technical data problems while ensuring that key business drivers are captured in collaboration with product management

• Extract, load, transform, clean and validate data

• Support and debug data pipelines

JOB REQUIREMENTS

We are trying to reimagine the way we help and interact with our customers, so we are looking for candidates with creativity, an open mind and a positive energy.

Our detailed requirements are as below:

• At least 4 years of experience in total at Data Engineering or at a similar role

• Strong Cloud-based Data Engineering experience in one of the following Clouds (AWS/Azure/GCP); we mainly use GCP but we are open to your Cloud experience (with at least 2 years of working on Cloud)

- As GCP Cloud Data Engineer: You must be strong at General Infrastructure and Services and particular data services such as Big Query, Dataflow, Airflow, Cloud Function, etc.

- As AWS Cloud Data Engineer: You must be strong at AWS technologies as the followings: data pipeline (Lake Formation, MWAA, EMR, S3, Glue and Athena); Data Warehousing technologies (AWS Redshift)

- As Azure Cloud Data Engineer: You must be strong at Azure Data Lake Storage, Azure Databricks and Azure Data Factory, Synapse, etc.

• Proven successful design and implementation of large and complex data solutions (Data Warehouse, Data Lake) using various architectural patterns such as Microservices

• Experience with Advanced SQL and Python skills

• Experience with DataOps

• Experience in using DevOps while working on Cloud data platforms like using Terraform for Infrastructure as Code (IaC), GitOps or using Docker, Kubernetes

• Good education background of Information Technology (IT) and Information and Communication Technology (ICT)

• Ability to influence both technical and business peers and stakeholders

• Good command of English verbal communication

• If you have work experience with Marketing domains, you will be preferred

You are not expected to have 100% of these skills. At HCLTech, a growth mindset is at the heart of our culture, so if you have most of these things in your toolbox, we would love to hear from you.

WHY YOU SHOULD JOIN US

• Hybrid working mode (3 working days at office, flexible time)

• Salary: Please completely feel free to tell us your expected number!!! HCL Technologies

• 18 paid leaves/year (12 annual leaves and 6 personal leaves)

• Insurance plan based on full salary + 13th month salary + Performance bonus

• Meal allowance of 730,000 VND/month

• 100% full salary and benefits as an official employee from the 1st day of working

• Medical benefit for employee and family

• Working in a fast-paced, flexible, and multinational working environment. Chance to travel onsite (in 49 countries)

• Free snacks, refreshment, and parking

• Internal training (Technical & Functional & English)

Working time: 08:30 AM - 06:00 PM from Mondays to Fridays (meal breaks included)