Data Engineering Lead

2 weeks ago

Sydney, New South Wales, Australia beBeeEngineering Full time $80,000 - $150,000
Job Title

Data Engineering Lead

About the Role

We are seeking a seasoned Data Engineering Lead to spearhead the development of our insurance data asset. The ideal candidate will have expertise in ETL processes, AWS technologies, and Agile methodologies.

This is an exciting opportunity to work at the forefront of data engineering, leveraging advanced knowledge of big data technologies and container orchestration tools.

The successful candidate will collaborate with cross-functional teams, working closely with stakeholders to design, implement, and maintain data assets that drive business insights.

Key Responsibilities
  • Develop and lead data engineering strategies to enhance data quality, availability, and accessibility
  • Collaborate with data scientists and analysts to identify data requirements and design optimized data pipelines
  • Maintain high-quality data assets, ensuring data integrity and adherence to regulatory frameworks
  • Utilize AWS suite of tools and infrastructure to ensure scalability, reliability, and performance
  • Work closely with stakeholders to develop end-to-end data solutions that meet business needs
Requirements
  • Strong background in data engineering, including ETL processes and big data technologies
  • Proficiency in AWS data technologies (EC2, EMR, S3, Redshift, EKS, Glue) and container orchestration tools (Docker, Kubernetes)
  • Experience with relational and NoSQL databases, query optimization, and data modeling
  • Excellent problem-solving skills, with ability to manage multiple stakeholders and projects
  • Effective communication and collaboration skills, with experience working in agile environments
Nice To Have
  • 5+ years of experience in commercial insurance data engineering
  • Familiarity with Advanced Analytics, Multi-Variate Statistics, and Machine Learning concepts
  • Demonstrated ability to bridge between business and technical teams, driving data-driven decision making

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