Solution Architect

Things to remember before sourcing Profiles:-

1. Early Joiners ( Immediate only)
2. Experience must be 10 to 12 years.
3. Very Strong at Data Science tools & Data Engineering.
4. Must have strong technology exposure with hands on solution design & architecture at enterprise level applications.

JD for Sr. Architect Data Science

• 9-11 years’ experience building solutions on Data Science platforms and applications with minimum of 2+ solution architecture experience.

• 3+ years’ Experience with Databricks, AWS Data lake, Spark, Python, Scala, R, Neo4J, Linux and ML processes.

Experience with architecture, design and implementation experience in big data technologies such as data science solutions. Expert programming experience in Python, R, Scala

Extend/Enhance production data systems to evolve with complex business needs

Deep Specialty Expertise in at least in few of the following areas:

• Experience with scaling big data workloads that are performant and cost effective

• Experience with Development Tools for CI/CD, Unit and Integration testing, Automation and Orchestration

• Experience designing data solutions on cloud infrastructure and services, such as AWS and/or Azure, utilizing best practices in cloud security and networking

• Experience with ML concepts covering Model Tracking, Model Serving and other aspects of productionizing ML pipelines in distributed data processing environments like Apache Spark, using tools like MLflow

Experience with data visualization tools is a plus (PowerBI, Tableau).

Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine learning algorithms is a plus