Data Engineer
Melbourne, AU
Xero
Xero software for small businesses connects you to your bank, accountant, bookkeeper, and other business apps. Start a free trial today.How you’ll make an impact
As a data engineer in the Marketing Data Science, Analytics & Insights team, you will be responsible for engineering large and complex data sets, as well as build robust, reusable and optimized data pipelines. You will have broad technical skills of developing and implementing data pipelines as well as data infrastructure to support the implementation of data transformation for analytics, business intelligence, machine learning models and other data projects.
What you’ll do
- Create integration between Xero’s Kafka infrastructure, Customer Data platform and other OLAP systems
- Deploy data pipelines following DevOps principles and incorporating automated code & data testing.
- Demonstrates a focus on continual self improvement, across both the technical and business aspects of delivering high quality data enrichment solutions
- Provide support to data quality and data validation through analysis of data and assisting in understanding the meaning of data
- Help drive continuous improvements to data quality procedures and a consistent approach to how data quality is measured, monitored and reported.
- Work on incident management, service requests, enhancements/changes and audits
What you’ll bring with you
- Strong data and technical background demonstrating innovation, initiative and a passion for data
- Confidence in collecting, collating and interpreting business requirements in order to produce quality outcomes
- Good time management with the ability to multitask, prioritize and deliver to schedule
- Highly motivated and proactive nature, constantly looking at methods for improvement
- Solution focused and has strong attention to detail
- Experience working with Business Owners and different stakeholders to gather data requirements and provide solutions
- CI/CD tools like Teamcity, GitHub Actions Jenkins, Harness or Circle.c
- Infrastructure as code utilities like Terraform, Cloudformation.
- Docker and Kubernetes.
- Good knowledge of SQL, Snowflake, dbt, Python, AWS, AWS Serverless (Lambda Functions), SQS, -SNS, S3, Glue,
- Clear and concise oral & written communication including technical documentation
- Experienced in orchestration tools (such as Apache Airflow, Prefect)
- Proficient in roll out and maintenance of cloud infrastructure
- Knowledge of data requirements for ML / AI use cases beneficial
- CDP implementation experience is plus
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow AWS Business Intelligence CI/CD CloudFormation Data pipelines Data quality dbt DevOps Docker Engineering GitHub Jenkins Kafka Kubernetes Lambda Machine Learning ML models OLAP Pipelines Python Snowflake SQL Terraform Testing
Perks/benefits: Career development Flex hours Health care Parental leave
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