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 solid understanding of how engineered datasets are consumed for analytics, including designing reporting-ready datasets and supporting BI and analytics teams.

It would be desirable if:

• You have experience with PySpark, Apache Spark, or shell scripting.

• You have exposure to analytics tools such as Amazon QuickSight, Power BI, Tableau, or similar platforms.
• You have experience with Apache Iceberg, Apache Airflow, dbt, Docker, or Kubernetes.
• You have experience with Amazon EMR or Amazon MWAA (Managed Workflows for Apache Airflow).
• You have experience with Snowflake, Databricks, or Microsoft Fabric.
• You have experience using AI-assisted development tools such as GitHub Copilot, Claude Code, ChatGPT, or Amazon Q Developer.

Preferred Certifications:

• AWS Certified Data Engineer – Associate.

• AWS Certified Solutions Architect – Associate or Professional.

• AWS Certified Developer – Associate.

• Databricks Certified Data Engineer Associate or Professional.

• Equivalent certifications demonstrating strong capability in cloud-native data engineering.

Please note: This role is remote; however, we require candidates to be based locally in the Philippines. This is to support occasional onsite activities such as team events, client meetings, or equipment handover. Additionally, local residency is necessary for compliance with Philippines labor laws and employment regulations.

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Why work for Sharesource?

Our clients come from all walks of life and so do we. We hire hundreds of skillful individuals from a wide variety of backgrounds, genders, ages, and personalities to live out our diverse culture and make a positive impact on the world!

Our 5 Values:

• Make a social impact: We balance our work for client teams and for society by constantly making a positive impact.
• Be proactive: We encourage brave thinking and continuous improvement, and drive change through action.
• Create value: We create measurable values for our stakeholders: our teams, partners, suppliers, investors, and communities.
• Be fair, open and honest: We foster equality and inclusivity in a supportive environment that embraces diversity and celebrates achievements.
• Add fun, passion and love: We prioritise fun and passion, fostering higher engagement and a positive can-do attitude.

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What to Expect in the Process?

1. You'll go through 3–4 interviews plus a possible assessment with our client partner. This includes an initial chat, a culture-fit interview, and 1–2 conversations with our awesome client. The whole process usually takes 1–2 weeks, but we'll let you know if things need to move quicker.
2. Our best advice? Be yourself and enjoy the conversations. We'll keep you updated every step of the way, and you're always welcome to reach out for updates anytime.
3. If all goes well, we'll complete reference checks and requirements quickly—so we can get that job offer to you without delay.

We would be grateful if you have these already:

• Fit to Work/Health Card (Basic 5 employment medical tests)

• NBI Clearance

• Social IDs - PHIC, SSS, HDMF, TIN

• Character references with contact info

At Sharesource, we believe in the value of diversity and inclusion. We are committed to creating a diverse, respectful, and inclusive workplace, and we do not discriminate based on factors such as race, gender, religion, sexual orientation, or disability.