The Role:

We are looking for a Senior Data Engineer specializing in modern, cloud-native data platforms, with a strong focus on Amazon Web Services (AWS) and Python. You will be responsible for designing, building, and optimizing highly scalable and reliable ETL/ELT pipelines and data warehouses that power analytics, machine learning, and business intelligence for our clients.

What we’re looking for:

5+ years of professional experience in data engineering
Expert proficiency in Python for data manipulation, scripting, and pipeline development (e.g., Pandas, PySpark).
Deep hands-on experience with the AWS cloud platform, specifically the core services used for data ingestion, storage, and processing (S3, Glue, Lambda, EMR).
Proven experience working with modern data warehouses (Snowflake, Amazon Redshift, or Google BigQuery/Azure Synapse).
Solid expertise in SQL and complex query writing/optimization.
Strong understanding of containerization and orchestration concepts (Docker, Kubernetes).
Fluent English communication skills.
Located in CET timezone (+/- 3 hours), we are unable to consider applications from candidates in other time zones.

Nice-to-have:

Experience with Infrastructure as Code (Terraform or CloudFormation).
Proficiency with a modern orchestration tool like Apache Airflow.
Familiarity with data streaming technologies (Kafka, Kinesis, or Flink).
AWS certifications

Responsibilities:

Architect, implement, and maintain scalable data pipelines (ETL/ELT) using Python and native AWS services to ingest data from various sources (APIs, databases, streaming services) into data lakes and warehouses.
Serve as the subject matter expert for the core AWS data services, including S3, Glue, EMR, Kinesis/MSK, and Redshift or Amazon Aurora.
Design robust and efficient data models (e.g., star schema, snowflake, data vault) for analytical and reporting needs.
Perform performance tuning and query optimization on large datasets within cloud data warehouses to ensure fast data delivery.
Implement infrastructure as code (IaC) using Terraform or CloudFormation, and integrate data pipelines into modern CI/CD processes.
Establish data quality monitoring, logging, alerting, and governance standards across the data platform.

What we offer:

Get paid, not played

No more unreliable clients. Enjoy on-time monthly payments with flexible withdrawal options.

Predictable project hours
Enjoy a harmonious work-life balance with consistent 8-hour working days with clients.
Flex days, so you can recharge
Enjoy up to 24 flex days off per year without losing pay, for full-time positions found through Proxify.
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One seamless process, multiple opportunities
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Compensation
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Remote C Jobs in Australia

Senior Data Engineer (AWS & Python)

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