Senior AWS Data Engineer

Showtime Consulting; Sydney; On-site; AUD 140,000 - 190,000; Full time

Job summary

Showtime Consulting is seeking a Senior AWS Data Engineer to join a high-performing data and analytics team. This hands-on role focuses on designing, building, and supporting scalable data pipelines and curated data platforms on AWS.

You will work across large-scale enterprise environments, ingested data for reporting, analytics, and downstream applications. The ideal candidate brings strong AWS data engineering expertise, advanced SQL and Python skills, and experience with dbt and Airflow for

Qualifications

• Experience designing, building, and operating scalable data pipelines in enterprise environments.
• Strong AWS data platform experience (S3, Glue, Redshift, Athena, EMR, dbt).
• Advanced SQL and Python development skills.
• Experience with PySpark and/or Apache Spark.
• Hands-on experience with Teradata and Siebel CRM datasets.
• Experience with orchestration tools like Airflow.
• Solid understanding of data warehousing and modern data architecture concepts.
• Strong stakeholder engagement and communication skills.

Responsibilities

• Build and support AWS data pipelines and ETL/ELT workflows.
• Develop data ingestion and transformation solutions using SQL, Python, and PySpark.
• Create curated datasets for reporting, analytics, and downstream applications.
• Implement data quality, monitoring, and operational support processes.
• Collaborate with analysts, data scientists, and stakeholders to deliver data solutions.
• Support DataOps practices, CI/CD, documentation, and production deployments.
• Optimise pipeline performance and workflow orchestration.

Skills

Extensive Data Engineering experience

AWS data platform (S3, Glue, Redshift,

Athena

EMR

dbt

Advanced SQL

Python

PySpark / Apache Spark

Teradata and Siebel datasets

Airflow or orchestration tools

Data warehousing concepts

Stakeholder engagement

Tools

Airflow

Job description

Company Description

Showtime Consulting is a leading provider of Shielded Cloud and Digital Solutions across Australia and New Zealand. We specialise in delivering secure, enterprise-scale technology solutions across cloud, data, DevSecOps, platform engineering, and digital transformation programs. We partner with major organisations to build high-performing technology teams and deliver innovative cloud-native solutions that improve reliability, scalability, security, and operational efficiency.

The Role

We are seeking an experienced Senior AWS Data Engineer to join a high-performing data and analytics team. This is a hands‑on role focused on designing, building, and supporting scalable data pipelines and curated data platforms on AWS. You will work across large-scale enterprise environments, helping to ingest, transform, and deliver trusted data assets that support reporting, analytics, operational decision‑making, and downstream applications. The ideal candidate will bring strong AWS data engineering expertise, advanced SQL and Python skills, and experience building modern ETL/ELT solutions using AWS native services, dbt, and orchestration platforms such as Airflow.

Key Responsibilities

• Build and support AWS data pipelines and ETL/ELT workflows.
• Develop data ingestion and transformation solutions using SQL, Python, and PySpark.
• Create curated datasets for reporting, analytics, and downstream applications.
• Implement data quality, monitoring, and operational support processes.
• Collaborate with analysts, data scientists, and stakeholders to deliver data solutions.
• Support DataOps practices, CI/CD, documentation, and production deployments.
• Optimise pipeline performance and workflow orchestration.

What You'll Need

• Extensive Data Engineering experience in enterprise environments.
• Strong AWS data platform experience across S3, Glue, Redshift, Athena, EMR, and dbt.
• Advanced SQL and strong Python development skills.
• Experience with PySpark and/or Apache Spark.
• Hands‑on experience with Teradata and Siebel CRM datasets.
• Experience with Airflow or similar orchestration tools.
• Solid understanding of data warehousing and modern data architecture concepts.
• Strong stakeholder engagement and communication skills.

Desirable Skills

• Telecommunications industry experience.
• Experience with real‑time or streaming data pipelines.
• Exposure to Lakehouse and modern analytics architectures.
• Experience with automated testing and DataOps practices.
• Experience working on large‑scale transformation programs.

Why Join Us?

• Work on enterprise-scale AWS data and analytics initiatives.
• Build modern cloud-native data platforms and pipelines.
• Collaborate with experienced data, cloud, and engineering specialists.
• Influence data engineering standards and best practices.
• Gain exposure to cutting‑edge AWS and DataOps technologies.