Job Description
What you'll do:
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Contribute to the development and maintenance of a scalable, secure, and efficient data platform.
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Provide tools and support for data ingestion, transformation, data product publication, management of ML lifecycle and AI services.
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Implement and follow industry standards in platform engineering to improve platform performance and reliability.
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Contribute in a collaborative team that prioritises continuous improvement, shared understanding and reliable systems
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Promote data quality, compliance, privacy, and security, along with AI innovation through platform design and support
What You’ll Bring
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Software Development Experience: Proven ability to support software development lifecycles with CI/CD practices, automated testing and full stack deployment in a cloud environment.
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Experience and understanding of the limitations and advantages working across varied architectural paradigms and design patterns.
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Solid understanding of platform observability and monitoring patterns and technologies.
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Data Technologies: Foundational understanding of tools like Snowflake, dbt, Apache Kafka, and knowledge of cloud platforms.
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Familiarity with technology governance and compliance frameworks and technology risk management.
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Core comprehension of security, integrity, and availability outcomes for platforms or services.
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Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience in a similar capacity.
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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.
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.