Senior Data Engineer
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Before you apply
SalaryA$125k – A$175k
LocationSydney, Australia
Work moderemote
Typefull-time
SenioritySenior
Experience3+ yrs
Company size2+ people
PostedJan 8, 2026 · 10mo ago
Verified live19h ago
May no longer be actively hiring
Posted by the company on Jan 8, 2026
At a glanceSummarised by Seekless from the posting.
3+ years of experience in data engineering, big data, or cloud data solutions
Proficiency in Python, Scala, or SQL for building scalable data pipelines
Experience with Databricks, Apache Spark, and Delta Lake
Familiarity with cloud platforms (AWS, Azure) and modern data architectures
Understanding of ETL processes, data lakes, and warehouse solutions
Excellent problem-solving skills
A passion for automation, AI, and optimising data workflows
Databricks Certification (e.g., Databricks Certified Data Engineer or ML Associate)
Experience with real-time streaming architectures (Kafka, Kinesis, or similar)
Knowledge of AI/ML pipelines and MLOps best practices
Prior experience in a consulting or client-facing role
Skills
Python
Scala
SQL
Databricks
Apache Spark
Delta Lake
AWS
Azure
Kafka
Kinesis
AI/ML pipelines
MLOps
Benefits
Competitive compensation
Performance bonuses
Flexible work culture
Remote work
Professional development
Training programs
About the role
Our client is looking for a Sr. Data Engineer who thrives on solving complex data challenges, designing robust architectures, and optimising big data pipelines. You’ll work with cutting-edge cloud and AI solutions, ensuring that data is accessible, scalable, and analytics-ready.
This role blends deep technical expertise, strategic problem-solving, and hands-on implementation. You’ll build and optimise ETL pipelines, data lakes, and data platforms while collaborating with cross-functional teams to drive AI-powered insights.
Responsibilities
•
Build scalable data architectures – Design and implement high-performance data pipelines and cloud-native solutions.
•
Optimise big data processing – Develop efficient and cost-effective data solutions using Databricks, Apache Spark™, and Delta Lake.
•
Ensure data quality and governance – Implement best practices for data validation, lineage, and security.
•
Drive automation and efficiency – Use Python, Scala, or SQL to automate data workflows and streamline processes.
•
Collaborate with cross-functional teams – Work with data scientists, analysts, and engineers to deliver data-driven solutions.
•
Stay ahead of the curve – Continuously explore new data engineering trends, AI advancements, and cloud technologies.
Qualifications
•
3+ years of experience in data engineering, big data, or cloud data solutions.
•
Proficiency in Python, Scala, or SQL for building scalable data pipelines.
•
Experience with Databricks, Apache Spark™, and Delta Lake.
•
Familiarity with cloud platforms (AWS, Azure) and modern data architectures.
•
Understanding of ETL processes, data lakes, and warehouse solutions.
•
Excellent problem-solving skills – Able to tackle complex data challenges with innovative solutions.
•
A passion for automation, AI, and optimising data workflows.
Preferred Qualifications
•
Databricks Certification (e.g., Databricks Certified Data Engineer or ML Associate).
•
Experience with real-time streaming architectures (Kafka, Kinesis, or similar).
•
Knowledge of AI/ML pipelines and MLOps best practices.
•
Prior experience in a consulting or client-facing role.
Benefits
•
Be part of an AI-native company – We live and breathe cutting-edge AI and data solutions.
•
Work on high-impact projects – We partner with industry leaders to solve some of the toughest data challenges.
•
Shape the future of data engineering – Be at the forefront of AI-driven transformation.
•
Competitive compensation – We offer a generous salary and performance-based bonuses.
•
Flexible work culture – Hybrid and remote work options to fit your lifestyle.
•
Grow with us – Access top-tier learning resources, training, and leadership development programs.
Compensation
The base pay range for this role is A$125,000 – A$175,000 per year.
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