Your Role and Responsibilities:As a Software Developer: Generalist, you will design, develop, test, and deliver offerings using leading-edge and/or proven technologies. You will work in an Agile, collaborative environment to understand stakeholder requirements and contribute to the development of innovative software solutions.
Your Primary Responsibilities Will Include:
Contribute to evolving existing source data pipelines to an ELT model of data ingestion.
Implement the separation of source-aligned data products from aggregate data products.
Decorate your data products with metadata to support knowledge transfer, adoption, and the application of Machine Learning and LLMs.
Develop and build Data & AI applications and intelligent features, leveraging large language models (LLMs) to enhance data products, under technical guidance.
Implement new data pipelines and good to support the training, fine-tuning, and deployment of AI/ML models.
Tag and classify your data assets to ensure they are used responsibly throughout the organization, applying masking or restricting access where appropriate.
Apply software engineering best practices to your code release process to support CI/CD and a high velocity collaboration model based on InnerSource, including MLOps principles.
Register and maintain the catalog entries for your data products and models to support discoverability and reuse.
Ensure your data products easily join with other business data products using common identifiers and keys.
Develop automated and resilient processes that support the end-end delivery of business value.
Contribute to defining and delivering on a data product SLO for your data 'customers'.
Responsibly share your data products with other internal consumers while balancing the core needs of security and compliance.
Contribute feedback and recommendations to the Data Platform team in order to remove friction and increase scale for all users.
Write custom adapters to integrate internal data sources into the centralized Warehouse environment.
Support and learn from team members on best practices in AI application development and data governance.
Required Education:
Bachelor's Degree
Preferred Education:
Bachelor's Degree
Required Technical and Professional Expertise:
What you will bring
Solid software, data, and AI/ML engineering skills that contribute to maintainable data products and intelligent applications.
Experience in developing and deploying applications utilizing Large Language Models (LLMs).
Familiarity with leading generative AI platforms and models, such as Codex, Claude, Gemini, or other equivalent open-source or proprietary LLMs.
Advanced proficiency in using SQL for data transformation.
Proficiency in at least one general purpose programming language, eg. Python (preferred for AI/ML), Go, Java, Rust, etc.
A collaborative approach, actively participating in technical debates and being open to different perspectives.
Focus on quality in all aspects of work, from code through to data.
Empathy for the users of your data products, leading to a focus on increasing adoption and delivering business results.
Ability to prioritize work to maximize contributions and impact.
Bias for action and a proactive approach.
Past experience in building data products, ideally with some exposure to governance and compliance requirements.
The following experience is considered a plus
Familiarity with open source or inner source development and processes
Familiarity of data mesh architectural principles
Experience with MLOps frameworks and tools.
Experience with Snowflake, Fivetran, dbt, Airflow / Astronomer
Preferred Technical and Professional Experience:
What you will bring
Solid software, data, and AI/ML engineering skills that contribute to maintainable data products and intelligent applications.
Experience in developing and deploying applications utilizing Large Language Models (LLMs).
Familiarity with leading generative AI platforms and models, such as Codex, Claude, Gemini, or other equivalent open-source or proprietary LLMs.
Advanced proficiency in using SQL for data transformation.
Proficiency in at least one general purpose programming language, eg. Python (preferred for AI/ML), Go, Java, Rust, etc.
A collaborative approach, actively participating in technical debates and being open to different perspectives.
Focus on quality in all aspects of work, from code through to data.
Empathy for the users of your data products, leading to a focus on increasing adoption and delivering business results.
Ability to prioritize work to maximize contributions and impact.
Bias for action and a proactive approach.
Past experience in building data products, ideally with some exposure to governance and compliance requirements.
The following experience is considered a plus
Familiarity with open source or inner source development and processes
Familiarity of data mesh architectural principles
Experience with MLOps frameworks and tools.
Experience with Snowflake, Fivetran, dbt, Airflow / Astronomer
Years of Experience:
4 - 8
