Senior Data Engineer-Gcp

Ampstek; Sydney; On-site; AUD 150,000 - 190,000; Full time

Job summary

Ampstek is seeking a Senior Data Engineer in Sydney to design, build, and optimize scalable data pipelines on Google Cloud Platform. You will enable data-driven decision-making by delivering reliable, high-quality data solutions across the organization.

You will lead pipelines for real-time and batch processing, collaborate with data scientists and stakeholders, and mentor junior engineers while upholding governance and security standards.

Qualifications

• 10+ years of experience in data engineering or related roles.
• Hands-on with Google Cloud Platform services (BigQuery, Dataflow, Pub/Sub).
• Proficiency in Python and SQL; distributed data processing (Beam, Spark).
• Experience designing real-time and batch data pipelines.
• Strong data modeling, data warehousing, and ETL/ELT concepts.

Responsibilities

• Design and implement scalable data pipelines using GCP services.
• Build and maintain data lakes, data warehouses, and ETL/ELT workflows.
• Work with large-scale structured and unstructured datasets.
• Optimize data processing pipelines for performance, cost, and reliability.
• Collaborate with data scientists, analysts, and stakeholders to deliver data solutions.
• Develop and enforce data quality, governance, and security standards.
• Automate data workflows with Airflow/Cloud Composer; ensure high availability.
• Monitor and troubleshoot production data pipelines and issues.
• Mentor junior engineers and share best practices.

Skills

GCP

BigQuery

Dataflow

Pub/Sub

Python

SQL

Apache Beam

Spark

Data modeling

ETL/ELT

CI/CD

DevOps

Data governance

Security

Education

Bachelor's degree in Computer Science, Engineering, or equivalent

Tools

Airflow

Cloud Composer

Docker

Job description

Job Description

Location: Sydney

Role Overview

We are looking for a highly experienced Senior Data Engineer with strong expertise in Google Cloud Platform

(GCP) to design, build, and optimize scalable data pipelines and architecture. The role will focus on enabling data-

driven decision-making by delivering high-quality, reliable, and efficient data solutions across the organization.

Key Responsibilities

• Design and implement scalable and robust data pipelines using GCP services
• Build and maintain data lakes, data warehouses, and ETL/ELT workflows
• Work with large-scale structured and unstructured datasets
• Optimize data processing pipelines for performance, cost, and reliability
• Collaborate with data scientists, analysts, and business stakeholders to deliver data solutions
• Develop and enforce data quality, governance, and security standards
• Automate data workflows and orchestration using tools like Apache Airflow / Cloud Composer
• Ensure high availability and fault tolerance of data platforms
• Monitor and troubleshoot data pipelines and production issues
• Mentor junior engineers and contribute to best practices

Must Have Skills & Experience

• 10+ years of experience in data engineering or related roles
• Strong hands-on experience with Google Cloud Platform (GCP) services such as:
• o BigQuery
• o Dataflow
• o Pub/Sub
• Expertise in Python, SQL, and distributed data processing frameworks (e.g., Apache Beam, Spark)
• Experience designing real-time and batch data pipelines
• Strong understanding of data modeling, data warehousing, and ETL/ELT concepts
• Experience with CI/CD pipelines and DevOps practices
• Familiarity with data governance, data security, and compliance frameworks
• Proven ability to work with large datasets in a cloud environment
• Strong problem-solving and performance optimization skills

Nice to Have

• Experience with multi-cloud environments (AWS/Azure)
• Knowledge of containerization (Docker, Kubernetes)
• Experience with streaming frameworks (Kafka, Pub/Sub streaming)
• Exposure to Machine Learning pipelines (Vertex AI)
• Certifications such as:
• o Google Professional Data Engineer
• Experience in domain-specific industries (telecom, finance, healthcare, etc.)
• Familiarity with data cataloging and governance tools
• Strong analytical and problem-solving skills
• Excellent communication and stakeholder management
• Ability to translate business requirements into technical solutions
• Leadership and mentoring capabilities
• Focus on scalability, reliability, and performance