Cloud Raptor is a up-to-date technology and digital transformation partner helping organisations design, build, and scale intelligent, future-ready solutions. We exist to close the gap between business ambition and technology execution—delivering outcomes that are measurable, secure, and built to last.

Our teams bring together experienced consultants, product specialists, and certified engineers with deep expertise across cloud platforms, enterprise software engineering, DevOps, AI/ML, cybersecurity, and large-scale digital transformation. We work closely with our clients to modernise legacy environments, optimise operations, and launch digital products that create real competitive advantage.

We support organisations across BFSI, Retail, Utilities, Education, and the Public Sector, delivering tailored solutions that align with each client’s strategic goals, risk profile, and growth roadmap. Our approach blends strong domain knowledge with pragmatic delivery—ensuring technology decisions translate into real business value.

Headquartered in Australia, with delivery hubs across India, the Philippines, the UK, the US, and the UAE, Cloud Raptor combines global scale with strong local expertise. Whether modernising core platforms, scaling cloud infrastructure, or building AI-driven products, we help organisations move faster with confidence.

At our core, Cloud Raptor is built on long-term partnerships, continuous learning, and outcome-driven delivery. We don’t just implement technology—we help shape what’s next. Let’s calibrate your future with technology.

– Data Engineer

Position Title: Data Engineer

Location: Sydney (Hybrid)

Client : Enterprise BFSI

Employment Type: Permanent About the Role

Cloud Raptor is seeking a highly skilled Data Engineer to design, build, and maintain scalable data solutions supporting enterprise analytics, reporting, and digital transformation initiatives. The successful candidate will have strong experience across the AWS ecosystem, modern data engineering practices,



and cloud-native data platforms.

You will work closely with business stakeholders, architects, data analysts, and engineering teams to deliver robust, high-performing data pipelines and data products. Key Responsibilities

•Design, develop, and maintain scalable data pipelines using AWS services.

•Build and manage ETL/ELT processes to support enterprise data platforms.

•Develop data ingestion frameworks for batch and streaming data sources.

•Create and optimize data models and transformations within Snowflake.

•Integrate real-time and event-driven data solutions using Kafka.

•Implement automated testing and quality controls across data pipelines.

•Maintain secure and compliant data storage solutions within AWS.

•Collaborate with architects and stakeholders to define technical solutions and data requirements.

•Monitor, troubleshoot, and optimise data processing performance and reliability.

•Support CI/CD deployment practices and infrastructure automation where required.

Technical Skills & Experience Essential Must have:

•Aws Data Services

•Glue Streaming

•PySpark

•Data Modeling Nice to Have

•Tableau

•Airflow Complimentary

•Observability

•CICD

•Terraform

•Strong experience with the AWS data ecosystem including:

oAWS Glue o Amazon S3

oIAM oLambda (desirable)

oCloudWatch oEvent-driven architectures

•Advanced Python development skills for data engineering applications.

•Demonstrated experience designing and building ETL/ELT pipelines.

•Strong experience with Snowflake data warehouse development and optimisation.

•Hands-on experience implementing data quality,



validation, and automated testing frameworks.

•Experience working with Apache Kafka for real-time data streaming and integration.

•Strong SQL development and performance tuning expertise.

•Experience working within Agile delivery environments.

•Understanding of secure and scalable cloud architecture principles. Desirable

•Experience with Infrastructure as Code (Terraform, CloudFormation).

•Experience with Databricks or Spark.

•Exposure to DevOps and CI/CD toolsets.

•Financial Services, Banking, Insurance, or Wealth Management experience.

•Knowledge of Data Governance and Data Quality frameworks. Key Competencies

•Strong analytical and problem-solving skills.

•Excellent stakeholder engagement and communication skills.

•Ability to work independently and across cross-functional teams.

•Continuous improvement mindset.

•Strong attention to detail and commitment to data quality. Qualifications

•Degree in Computer Science, Information Technology, Engineering, Mathematics, or related discipline.

•AWS Certification (Associate or Professional) highly regarded.

•Snowflake Certification beneficial.

What Success Looks

Like

•Reliable, scalable, and secure data pipelines delivered to production.

•High-quality tested data assets supporting business outcomes.

•Optimised Snowflake environments delivering performance and cost efficiencies.

•Robust real-time integration capabilities leveraging Kafka.

•Strong collaboration with engineering and business stakeholders to drive data-driven decision making.

Ideal Candidate

You are a hands-on Data Engineer who enjoys building modern cloud-based data platforms. You bring deep AWS expertise, strong Python engineering skills, and experience delivering enterprise-grade ETL solutions. You thrive in fast-paced environments and are passionate about creating reliable, scalable, and high-quality data products that enable business success.

📌 Data Engineer (Sydney)
🏢 Cloud Raptor
📍 Sydney