Lead Python Developer @ Netscribes

Job Description

Location: Mumbai (Hybrid)
Notice Period: less than 30 days
Workdays: Monday to Friday
Work timings: 10 am to 7 pm

Roles & Responsibilities

• Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles & business goals
• Solve complex data problems to deliver insights that help our business to achieve their goals
• Works with Data scientists to select and test suitable models
• Deploys model and data pipelines using DevOps practices
• Works on Data scraping and data cleaning tasks
• Responsible for Data enrichment & feature extraction.
• Implementation and deployment of emerging tools and processes for analytic data engineering in order to improve our efficiency as a team
• Participates in multifunctional teams and makes insightful contributions as a data engineer

Qualification:

• Academics: Bachelors in Computer Science, MIS, or Engineering preferred
• Prior Experience: 5 to 8 years of experience in a data engineering role
• Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space
• Experience in building robust data pipelines and deploying/maintaining them by applying DevOps principles
• Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space (preferred)
• Experience with containerization and managing pipelines and microservices, e.g., Docker, Kubernetes, Airflow
• Expertise in programming Languages - Python
• Must have experience of working on GCP /e-com platforms particularly working with unstructured data
• Must have experience in running use cases in the sales analytics/ eCommerce domain

Technology Expertise

• SQL Implementation on GCP and / or e-com platforms
• Database development experience using BigQuery/Redshift and experience with a variety of relational, NoSQL, and cloud database technologies
• ML frameworks added advantage - Tensorflow, Pytorch.etc.
• Basic proficiency on ML techniques - clustering, decision tree learning, naive Bayes, support vector machines, Q-learning, temporal difference, adversarial networks, and neural networks
• Basic proficiency of data visualization techniques & tools - Visualizing complex insights using Plotly, matplotlib, ggplot2, etc; experience with dashboarding tools desired (e.g., Shiny, Dash, Tableau)
• Experience in Dataiku/Databricks is a plus.
• Python Data manipulation & Scraping libraries should be known (Beautiful soup, Scrapy.etc)

Interested candidates can share their CVs on the below-mentioned email:

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Keyskills:   python data cleaning data architects data scraping