Technology Lead

XPT Software; Melbourne; On-site; AUD 120,000 - 180,000; Full time

Job summary

XPT Software in Melbourne is seeking an experienced Data Engineer to design and maintain robust data pipelines using GCP, BigQuery and Kubernetes/GKE. You will work on batch, streaming, and near-real-time ingestion, with a focus on scalable ETL/ELT processes and reliable data quality.

You should have strong SQL skills, good communication, and a practical understanding of SDLC. This role offers a collaborative team environment and modern cloud-based tooling.

Qualifications

• Strong understanding of SDLC process.
• Should have Strong understanding and trouble shooting skills
• Must have strong experience in building, enhancing, and maintaining data pipeline frameworks
• Must be able to design reusable data engineering frameworks, accelerators, and templates to standardize ingestion, transformation, orchestration, and data quality controls.
• Must have hands-on experience with GCP data services such as BigQuery, Kubernetes/GKE ,Cloud Dataflow, Dataproc, Pub/Sub, and Cloud Storage.
• Must demonstrate proficiency in ETL/ELT development, SQL-based transformations, and distributed data processing.
• Must implement production-grade pipelines with appropriate error handling, logging, monitoring, and performance optimization.

Responsibilities

• Strong understanding of SDLC process.
• Should have Strong understanding and trouble shooting skills

Skills

GCP BigQuery

Kubernetes/GKE with SQL Knowledge

Job description

Must Have Skills: GCP big query , Kubernetes/GKE with SQL Knowledge

Nice to Have Skills:

GCP Certified

Detailed Job Description:

Good communication skills with knowledge on SQL, GCP big query , Kubernetes/GKE

• Strong understanding of SDLC process.
• Should have Strong understanding and trouble shooting skills

Core requirements:

• Must have strong experience in building, enhancing, and maintaining data pipeline frameworks supporting batch, streaming, and near-real-time processing.
  
• Must be able to design reusable data engineering frameworks, accelerators, and templates to standardize ingestion, transformation, orchestration, and data quality controls.
  
• Must have hands-on experience with GCP data services such as BigQuery, Kubernetes/GKE ,Cloud Dataflow, Dataproc, Pub/Sub, and Cloud Storage.
  
• Must demonstrate proficiency in ETL/ELT development, SQL-based transformations, and distributed data processing.
  
• Must implement production-grade pipelines with appropriate error handling, logging, monitoring, and performance optimization.