- Build scalable AWS data pipelines and datasets.
- Develop solutions using SQL, Python, PySpark, and dbt.
- Support enterprise analytics, reporting, and data platforms.
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.
