Data and MLOps Engineer | Python, Snowflake

5 - 10 years

11 - 16 Lacs

Posted:3 weeks ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Your Impact

* Run data pipelines in monthly cadence, owning the quality of the output

* Clean data and maintain pipelines, and make changes to safeguard data quality and reduce execution risks

* Work closely with data science team to develop new features and enable access for ad hoc research

* Optimise running of slow or resource heavy pipelines, minimising unnecessary computation and reducing technical debt

* Aid in transition from pandas pipelines to snowflake environment

* Own and understand the datasets, their context and logic, and share knowledge with the data science team

* Perform exploratory research on datasets, uncovering new signals for the team to incorporate in models

* Develop quality dashboards and expose our data science products to stakeholders

* Collaborate with infrastructure team to develop and enable new MLOps capabilities and workflows

* Collaborate with Data Science team to deploy, monitor and maintain ML models, through implementing pipelines and workflows

Minimum Qualifications

* 5+ years of relevant experience with a Bachelors Degree in Computer Science or related subject

* Fluent in Python and SQL, and versed in debugging in an IDE such as VSCode

* Substantial experience working in Snowflake (or another cloud-based DB, e.g. BigQuery)

* GitHub/Bitbucket and version control, and a strong sense of coding standards and quality

* Experience building dashboards in tableau and python (e.g. with Streamlit or Flask)

* Good communication and planning skills, and ability to share knowledge across the team

* Demonstrated data wrangling and mining skills, including in real-time hackathon-like settings.

Preferred Qualifications

* Experience working in supply chain or demand planning related data (bookings, manufacturing, backlogs and lead times, etc.)

* Experience with Agile team and project planning

* Understanding of CI/CD pipelines and orchestration technologies such as Docker, Kubernetes, Openshift

* Experience with Spark/Pyspark, Polars

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