Senior Data Engineer (MSP)

Who is Sharesource?

We are a social enterprise dedicated to connecting global opportunities with talented individuals. Currently, we serve Australian clients and aim to empower businesses to thrive by accessing the talent they need worldwide. Our mission is to support individuals in achieving success in their careers while fostering a company culture that embodies our values.

What are we looking for?

We are seeking an experienced Senior AWS Data Engineer with 5+ years' experience designing, building, and supporting modern cloud-native data platforms.

The ideal candidate has strong experience across the full data engineering lifecycle, including ingestion, transformation, orchestration, storage, governance, operational support, and optimisation within an AWS-native environment. This role emphasizes leveraging AWS-managed services and applying modern cloud-native architecture, rather than lifting traditional ETL solutions into AWS.

While primarily focused on data engineering, the role also requires a strong understanding of downstream analytics and the ability to structure, curate, and optimise datasets for reporting, business intelligence, and advanced analytics.
What are you expected to do?

- Design, build, and support modern cloud-native data engineering platforms on AWS.

- Develop and maintain scalable ETL/ELT pipelines for data ingestion, transformation, and processing.

- Architect and manage data lake solutions to support structured, semi-structured, and unstructured data.

- Integrate data from multiple sources, including APIs, SaaS platforms, databases, streaming platforms, and file-based systems.

- Apply modern cloud-native design principles, leveraging AWS-managed services where appropriate.

- Ensure data platforms are reliable, scalable, and optimised for performance and cost-efficiency.

- Implement data governance, quality checks, validation processes, and monitoring frameworks.

- Provide operational support, including troubleshooting, issue resolution, and ongoing optimisation of data pipelines.

- Collaborate with analytics and business teams to structure and deliver reporting-ready datasets.

- Support downstream reporting, business intelligence, and advanced analytics use cases.

- Contribute to best practices, standards, and continuous improvement of data engineering processes.

You'll be a great fit if:

- You have 5+ years' experience delivering enterprise data engineering solutions.

- You have strong experience designing cloud-native data engineering solutions on AWS.

- You have experience designing and supporting modern data lake architectures.

- You have experience building scalable ETL/ELT pipelines.

- You have experience working with structured, semi-structured, and unstructured data.

- You have experience integrating data from APIs, SaaS platforms, databases, streaming platforms, and file-based sources.

- You have experience developing production-grade, operationally supported data platforms.

- You have experience implementing data quality, validation, monitoring, and operational support processes.

- You have strong practical experience with AWS technologies, including S3, Lake Formation, Glue, Lambda, Redshift, Athena, DMS, Kinesis, EventBridge, SQS, SNS, Step Functions, IAM, Secrets Manager, KMS, CloudWatch, and CloudTrail.

- You have strong experience with SQL, Python, ETL/ELT development, data pipeline design, orchestration, data modelling, source-to-target mapping, data quality frameworks, performance optimisation, and operational troubleshooting.

- You have experience with Git, GitHub, CI/CD pipelines, Infrastructure as Code (e.g. Terraform), automated deployments, logging and monitoring, and secure development practices.

- You have a strong understanding of modern cloud-native architectures, data lake design, analytical data platforms, data governance, metadata management, security, cost optimisation, performance optimisation, and high-availability design.

- You have a s