Job Description
Apply for Senior Data Engineer - AWS and Snowflake at Capgemini in Melbourne, VIC, AU. This full‐time on‐site position offers great opportunities for career growth.
n
About the Service Line
n
Capgemini Global Insights & Data business line is a market leader in Data Engineering, Cloud Data Platforms, Data Science, and AI and Advanced Analytics across all sectors including financial services, public sector, consumer products, telecommunication & energy resources.
n
Responsibilities
n
n
Design, develop, and maintain scalable real‐time, event‐driven, CDC‐based, and batch data pipelines on AWS and Snowflake to support analytics.
n
Build and optimize data ingestion frameworks leveraging streaming technologies, event‐based architectures, and Change Data Capture (CDC) patterns.
n
Develop and manage cloud‐native data solutions preferably AWS that ensure high availability, reliability, scalability, and performance.
n
Optimize Snowflake data models, queries, workloads, and storage strategies to improve performance and cost efficiency.
n
Implement and maintain robust data quality, data governance, security, privacy, and compliance controls across the data platform.
n
Design and manage ETL/ELT processes for integrating data from multiple internal and external sources.
n
Automate infrastructure provisioning, testing, deployment,



and monitoring using CI/CD pipelines and Infrastructure‐as‐Code practices.
n
Collaborate closely with solution architects, application development teams, data scientists, business analysts, and key stakeholders to deliver data solutions aligned with business objectives.
n
n
Qualifications
n
n
Solid hands‐on experience with Python and SQL for data engineering, transformation, and automation.
n
Extensive experience designing and implementing data solutions on AWS, including services such as S3, Glue, Lambda, EMR, Kinesis, EventBridge, Redshift, Step Functions, and related data services.
n
Strong expertise in Snowflake, including data modelling, performance tuning, workload optimization, security, and administration.
n
Experience building real‐time streaming, event‐driven, and CDC‐based data ingestion architectures.
n
Solid understanding of ETL/ELT frameworks, distributed data processing, and modern data engineering patterns.
n
Experience with DevOps practices, CI/CD pipelines, version control systems (e.g., Git), and infrastructure automation.
n
Knowledge of data governance, data quality frameworks, metadata management, security, and compliance requirements.
n
Experience working with large‐scale structured and unstructured datasets in cloud environments.
n
#J-*****-Ljbffr

📌 Senior Data Engineer - Aws And Snowflake At Capgemini (Victoria)
🏢 Capgemini
📍 Victoria