What you'll do:
Contribute to the development and maintenance of a scalable, secure, and efficient data platform.
Provide tools and support for data ingestion, transformation, data product publication, management of ML lifecycle and AI services.
Implement and follow industry standards in platform engineering to improve platform performance and reliability.
Contribute in a collaborative team that prioritises continuous improvement, shared understanding and reliable systems
Promote data quality, compliance, privacy, and security, along with AI innovation through platform design and support
What You’ll Bring
Software Development Experience: Proven ability to support software development lifecycles with CI/CD practices, automated testing and full stack deployment in a cloud environment.
Experience and understanding of the limitations and advantages working across varied architectural paradigms and design patterns.
Solid understanding of platform observability and monitoring patterns and technologies.
Data Technologies: Foundational understanding of tools like Snowflake, dbt, Apache Kafka, and knowledge of cloud platforms.
Familiarity with technology governance and compliance frameworks and technology risk management.
Core comprehension of security, integrity, and availability outcomes for platforms or services.
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience in a similar capacity.
Azure, AWS or other cloud development and varied data tooling certifications (e.g., AWS Solutions Architect Associate, AWS Certified Data Engineer, SnowPro certifications, Confluent Certified Developer for Kafka, etc) are highly regarded.
Active learning approach with demonstrated interest in staying up to date with software, Data and AI technology trends.
Adaptability: Willingness to continuously evolve processes and adopt innovative technologies to enhance team efficiency.