Data Engineer (AU Media, WFH)

Schedule: Monday to Friday (6:00AM - 3:00PM PHT)
 
What are we looking for?
 
Skills Required:

• At least 3 years of experience in cloud-based data solution development, data integration, and data warehousing.
• At least 3 years of hands-on experience with AWS services, including Amazon Redshift, Amazon S3, AWS IAM, AWS Glue, and AWS Lambda.
• Strong programming experience with SQL and Python.
• Practical experience implementing CI/CD pipelines, source control repositories, and automation best practices.
• Strong understanding of data modeling, schema design, and performance optimization.
• Experience preparing and maintaining technical documentation and support materials.
• Excellent written and verbal communication skills, with the ability to collaborate effectively across teams.
• Experience working within Agile development environments and methodologies.

Nice to Have:

• Proven experience working with Business Intelligence (BI) and data visualization tools.
• Familiarity with data governance frameworks, privacy regulations, and data security best practices.
• A tertiary qualification in Computer Science, Data Engineering, Information Technology, or a related field, or equivalent relevant industry experience.

What will you do?
 
Supporting & Interacting

• Develop collaborative relationships with stakeholders to enable the successful delivery of data-based solutions.
• Ensure the quick turnaround of critical support issues within production data environments.
• Provide technical guidance and coaching to peers.

Analysing & Interpreting

• Assess requirements for completeness and clarify where required.
• Contribute to team estimation of development work so business stakeholders can make informed decisions.
• Analyse data solution requirements, source system constraints, transformation logic, integration patterns and downstream reporting needs.
• Identify risks, dependencies, data quality issues and technical considerations that may affect delivery timelines, scalability, security or production reliability.

Organising & Executing

• Design, develop and implement enhancements to the data warehouse.
• Design, develop and implement real-time and batch scalable data pipelines from various sources using SQL and Python.
• Automate the build and deployment of data pipelines using CI/CD best practices.
• Develop reusable frameworks for solving common data integration needs.
• Ensure data compliance and data security needs are met in the design of solutions.
• Monitor, troubleshoot and optimise data pipelines, warehouse processes and production data workflows for reliability, quality and performance.
• Prepare and maintain technical and support documentation for data pipelines, data models, deployment processes and operational support procedures.

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Equal Employment Statement
Employment decisions at ConnectOS will be conducted without consideration of factors such as age', race, color, religion, gender, disability status, sexual orientation, gender identity or expression, genetic information, and marital status. ConnectOS ensures the full confidentiality of the data it processes.