What youll be doing
- Designing and maintaining data pipelines optimized for ML/AI workloads including handling of large-scale unstructured and semi-structured data.
- Building feature pipelines and feature stores that ensure reusability and consistency of data used by machine learning models.
- Collaborating with Data Scientists and ML Engineers to understand data requirements for training validation and production deployment.
- Ensuring data quality lineage and governance meet standards required for AI/ML applications.
- Supporting MLOps practices by integrating data pipelines with model training monitoring and deployment workflows.
- Leveraging distributed processing frameworks (e.g. Spark Databricks Azure Synapse) for scalable ML data processing.
Qualifications :
What you bring
- 8 years of experience as a Data Engineer working with Azure and Databricks ideally with exposure to ML/AI-related data workflows.
- College degree that demonstrates your analytic abilities such as Econometrics Computer Sciences Mathematics or similar;
- Excellent analytical and problem-solving skills;
- Experience with data preparation for ML/AI: managing large datasets feature engineering and real-time or batch data pipelines.
- Familiarity with MLOps concepts and how data engineering supports model lifecycle management.
- Experience with orchestration frameworks (Airflow Prefect or Azure Data Factory) for complex ML pipelines.
- Knowledge of unstructured data processing (text images logs) is a plus.
- Strong SQL and Python skills; experience with distributed data processing (PySpark Dask etc.) is a plus.
Why youll love working here
- Impact from day one Join a scale-up where your ideas shape how global businesses operate online.
- Continuous learning Access a structured onboarding rated 9.1/10 by previous hires mentorship and feedback culture.
- Hybrid flexibility Work from our office 3 days per week and from home 2 days.
- Career growth Expand your technical and leadership scope in a company built for long-term success.
Our values
At Sana Commerce our values drive everything we do:
- Champions of Our League We deliver lasting success balancing quick wins and long-term value
- Supercharge Our Customers Were revolutionizing B2B commerce together helping our customers to lead and succeed.
- Determined to Grow We embrace challenges growing and raising the bar for ourselves and our industry.
- Bold Together We dare to be bold because we have each others back.
Ready to build reliability that scales
Apply now and help shape the foundation of our next-generation SaaS platform.
Additional Information :
#LI-Hybrid
Remote Work :
No
Employment Type :
Full-time
What youll be doingDesigning and maintaining data pipelines optimized for ML/AI workloads including handling of large-scale unstructured and semi-structured data.Building feature pipelines and feature stores that ensure reusability and consistency of data used by machine learning models.Collaboratin...
What youll be doing
- Designing and maintaining data pipelines optimized for ML/AI workloads including handling of large-scale unstructured and semi-structured data.
- Building feature pipelines and feature stores that ensure reusability and consistency of data used by machine learning models.
- Collaborating with Data Scientists and ML Engineers to understand data requirements for training validation and production deployment.
- Ensuring data quality lineage and governance meet standards required for AI/ML applications.
- Supporting MLOps practices by integrating data pipelines with model training monitoring and deployment workflows.
- Leveraging distributed processing frameworks (e.g. Spark Databricks Azure Synapse) for scalable ML data processing.
Qualifications :
What you bring
- 8 years of experience as a Data Engineer working with Azure and Databricks ideally with exposure to ML/AI-related data workflows.
- College degree that demonstrates your analytic abilities such as Econometrics Computer Sciences Mathematics or similar;
- Excellent analytical and problem-solving skills;
- Experience with data preparation for ML/AI: managing large datasets feature engineering and real-time or batch data pipelines.
- Familiarity with MLOps concepts and how data engineering supports model lifecycle management.
- Experience with orchestration frameworks (Airflow Prefect or Azure Data Factory) for complex ML pipelines.
- Knowledge of unstructured data processing (text images logs) is a plus.
- Strong SQL and Python skills; experience with distributed data processing (PySpark Dask etc.) is a plus.
Why youll love working here
- Impact from day one Join a scale-up where your ideas shape how global businesses operate online.
- Continuous learning Access a structured onboarding rated 9.1/10 by previous hires mentorship and feedback culture.
- Hybrid flexibility Work from our office 3 days per week and from home 2 days.
- Career growth Expand your technical and leadership scope in a company built for long-term success.
Our values
At Sana Commerce our values drive everything we do:
- Champions of Our League We deliver lasting success balancing quick wins and long-term value
- Supercharge Our Customers Were revolutionizing B2B commerce together helping our customers to lead and succeed.
- Determined to Grow We embrace challenges growing and raising the bar for ourselves and our industry.
- Bold Together We dare to be bold because we have each others back.
Ready to build reliability that scales
Apply now and help shape the foundation of our next-generation SaaS platform.
Additional Information :
#LI-Hybrid
Remote Work :
No
Employment Type :
Full-time
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