Job Description
Senior Data Engineer – AWS and Snowflake
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Design, develop, and maintain scalable real‐time, event‐driven, CDC‐based, and batch data pipelines on AWS and Snowflake to support analytics.
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Build and optimise data ingestion frameworks leveraging streaming technologies, event‐based architectures, and Change Data Capture (CDC) patterns.
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Develop and manage cloud‐native data solutions preferably on AWS that ensure high availability, reliability, scalability, and performance.
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Optimise Snowflake data models, queries, workloads, and storage strategies to improve performance and cost efficiency.
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Implement and maintain robust data quality, governance, security, privacy, and compliance controls across the data platform.
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Design and manage ETL/ELT processes for integrating data from multiple internal and external sources.
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Automate infrastructure provisioning, testing, deployment, and monitoring using CI/CD pipelines and Infrastructure‐as‐Code practices.
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Collaborate closely with solution architects, application development teams, data scientists, business analysts, and key stakeholders to deliver data solutions aligned with business objectives.
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Experience and Qualifications
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Strong hands‐on experience with Python and SQL for data engineering, transformation, and automation.




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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.
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Strong expertise in Snowflake, including data modelling, performance tuning, workload optimisation, security, and administration.
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Experience building real‐time streaming, event‐driven, and CDC‐based data ingestion architectures.
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Solid understanding of ETL/ELT frameworks, distributed data processing, and modern data engineering patterns.
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Experience with DevOps practices, CI/CD pipelines, version control systems (e.g., Git), and infrastructure automation.
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Knowledge of data governance, data quality frameworks, metadata management, security, and compliance requirements.
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Experience working with large‐scale structured and unstructured datasets in cloud environments.
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Benefits
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Exposure to transformational programs in AI and Data portfolio.
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Growth opportunities through learning platforms, certifications, and global mobility.
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Inclusive culture backed by the "Inclusive Future for All" commitment.
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Competitive total rewards and recognition programs.
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📌 Senior Data Engineer - Aws And Snowflake At Capgemini (New South Wales)
🏢 Capgemini
📍 New South Wales