Cloud-Driven Backend Engineer | AWS Data & Analytics

Zensys; Council of the City of Sydney; Hybrid; AUD 120,000 - 180,000; Full time

Job summary

Zensys is seeking a data engineering professional to design and implement scalable data pipelines in the AWS cloud. The role involves building batch and streaming ETL using Python, PySpark, Airflow MWAA, and AWS data services to support analytics and data warehousing on Redshift.

You will also ensure secure data access via Secrets Manager and KMS, manage data lakes on S3, and collaborate with cross-functional teams to deliver reliable data solutions.

Qualifications

• Proficient in Python with Pandas, PySpark and boto3 for data processing.
• Hands-on design of workflows in Apache Airflow (MWAA).
• Experience with Amazon Redshift for analytics and data warehousing.
• Strong SQL skills and data modeling/transformations.
• Experience with Amazon S3 and data lake architectures.
• Familiarity with AWS core services: EC2, S3, IAM, Lambda.
• Experience using AWS Secrets Manager and AWS KMS for secure access.
• Understanding of batch (Glue, EMR) and streaming (Kinesis) processing.
• Version control with Git.

Skills

SQL

Data Modeling

Batch Processing

Streaming

Communication

Tools

Python

Pandas

PySpark

boto3

Airflow (MWAA)

Amazon Redshift

SQL

Amazon S3

AWS (EC2, IAM, Lambda)

AWS Secrets Manager

AWS KMS

AWS Glue

AWS EMR

Kinesis

Git

Job description

Zensys is seeking a data engineering professional to design and implement scalable data pipelines in the AWS cloud. The role involves building batch and streaming ETL using Python, PySpark, Airflow MWAA, and AWS data services to support analytics and data warehousing on Redshift.

You will also ensure secure data access via Secrets Manager and KMS, manage data lakes on S3, and collaborate with cross-functional teams to deliver reliable data solutions.