Key Responsibilities:
- Develop and optimize in technical landscape i.e. as Databricks Python frameworks and DAX.
- Enhance existing self-service models to support operational needs.
- Implement scalable solutions for data processing reporting and analytics.
- Work closely with the roadmap owner to execute initiatives according to the pipeline.
- Ensure data quality governance and performance of analytics tools.
- Support project delivery by providing technical input for timelines dependencies and resource planning.
Your profile - Bachelors or Masters degree (or equivalent experience) in Computer Science Data Science Statistics Engineering Mathematics or a related field.
- 5 years of hands-on experience in Data Analytics Data Science or AI-related IT roles
- Expert coding skills in Python and SQL with proven track record in large-scale data wrangling model development workflows and automation
- Practical experience designing and deploying machine learning models into production (supervised/unsupervised feature engineering model evaluation MLOps).
- Familiarity or basic knowledge of Jobs and Pipelines in Databricks and ability to architect scalable and automated workflows.
- Solid understanding of Azure cloud computing DevOps practices and CI/CD pipelines.
- Experience working with version control systems and collaboration tools (Azure DevOps Git).
- Strong communication and leadership skills with ability to mentor junior developers and present technical solutions to business stakeholders.
- Passion for driving innovation and creating AI-powered data solutions that go beyond traditional reporting.
- Strong problem-solving and technical design skills.
- Ability to collaborate with business leaders and translate requirements into solutions.
- Familiarity with Supply Chain data structures and operational reporting needs.
- Basic project management awareness for technical execution and coordination.
Key Responsibilities: Develop and optimize in technical landscape i.e. as Databricks Python frameworks and DAX. Enhance existing self-service models to support operational needs. Implement scalable solutions for data processing reporting and analytics. Work closely with the roadmap owner to execut...
Key Responsibilities:
- Develop and optimize in technical landscape i.e. as Databricks Python frameworks and DAX.
- Enhance existing self-service models to support operational needs.
- Implement scalable solutions for data processing reporting and analytics.
- Work closely with the roadmap owner to execute initiatives according to the pipeline.
- Ensure data quality governance and performance of analytics tools.
- Support project delivery by providing technical input for timelines dependencies and resource planning.
Your profile - Bachelors or Masters degree (or equivalent experience) in Computer Science Data Science Statistics Engineering Mathematics or a related field.
- 5 years of hands-on experience in Data Analytics Data Science or AI-related IT roles
- Expert coding skills in Python and SQL with proven track record in large-scale data wrangling model development workflows and automation
- Practical experience designing and deploying machine learning models into production (supervised/unsupervised feature engineering model evaluation MLOps).
- Familiarity or basic knowledge of Jobs and Pipelines in Databricks and ability to architect scalable and automated workflows.
- Solid understanding of Azure cloud computing DevOps practices and CI/CD pipelines.
- Experience working with version control systems and collaboration tools (Azure DevOps Git).
- Strong communication and leadership skills with ability to mentor junior developers and present technical solutions to business stakeholders.
- Passion for driving innovation and creating AI-powered data solutions that go beyond traditional reporting.
- Strong problem-solving and technical design skills.
- Ability to collaborate with business leaders and translate requirements into solutions.
- Familiarity with Supply Chain data structures and operational reporting needs.
- Basic project management awareness for technical execution and coordination.
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