We are looking for an experienced Data Engineer (9–14 Years) to join a high-performing team delivering enterprise-scale data platforms and real-time data solutions on AWS.
Must Have Skills
AWS Cloud Services
Python & PySpark
Apache Airflow (MWAA)
SQL
Amazon Redshift
AWS SageMaker Unified Studio
AWS Kinesis / Kafka (Real-Time Streaming)
Key Responsibilities
Design and develop scalable batch and real-time data ingestion frameworks.
Build and optimize data pipelines using AWS services and contemporary data engineering practices.
Develop low-latency streaming solutions using Kinesis, Kafka, or similar technologies.
Implement data transformations, orchestration workflows, and monitoring solutions.
Work with Data Warehouses, Data Lakes,
and Lakehouse architectures.
Collaborate with cross-functional teams to deliver robust and scalable data solutions.
Required Experience
Solid expertise in AWS, Python, PySpark, Airflow, and Redshift.
Hands-on experience with SageMaker Unified Studio.
Experience with relational and NoSQL databases (Oracle, MongoDB, DynamoDB, Snowflake, Teradata, etc.).
Proven experience building real-time and batch data pipelines.
Knowledge of CI/CD, Git, Infrastructure as Code (Terraform/CloudFormation).
Data Modelling experience is highly desirable.
📌 Data Engineer Nsw Sydney
🏢 The HR Ally
📍 Sydney
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