S&C Global Network - Decision Science Practitioner Analyst

Key Responsibilities

Data Science and Engineering

• Implement and manage end to end Data Quality frameworks usingCollibra Data Quality(CDQ). This includes requirement gathering from the client,code developmenton SQL, Unit testing, Client demos, User acceptance testing, documentation etc. Work extensively with business users, data analysts, and other stakeholders to understand data quality requirements and business use cases.
• Developdata validation, profiling, anomaly detection, and reconciliation processes.
• WriteSQL queries for simple to complex data quality checks.
• Python, and PySparkscripts to support data transformation and data ingestion.
• Deploy and manage solutions onKubernetesworkloads for scalable execution.
• Maintain comprehensivetechnical documentation of Data Quality processes and implemented solutions.
• Work in anAgile environment, leveragingJirafor sprint planning and task management.
• Troubleshoot data quality issues and collaborate with engineering teams for resolution.
• Provide insights forcontinuous improvement in data governance and quality processes.
• Build and manage robust data pipelines using Pyspark and Python to read and write from databases such as Vertica and PostgreSQL.
• Optimize and maintain existing pipelines for performance and reliability.
• Build custom solutions using Python, including FastAPI applications and plugins for Collibra Data Quality.
• Oversee the infrastructure of the Collibra application in Kubernetes environment, perform upgrades when required, and troubleshoot and resolve any Kubernetes issues that may affect the application's operation.
• Deploy and manage solutions, optimize resources for deployments in Kubernetes, including writing YAML files and managing configurations
• Build and deploy Docker images for various use cases, ensuring efficient and reusable solutions.

Collaboration and Training

• Communicate effectively with stakeholders to align technical implementations with business objectives.
• Provide training and guidance to stakeholders on Collibra Data Quality usage and help them build and implement data quality rules.

Version Control and Documentation

• Use Git for version control to manage code and collaborate effectively.
• Document all implementations, including data quality workflows, data pipelines, and deployment processes, ensuring easy reference and knowledge sharing.

Database and Data Model Optimization

• Design and optimize data models for efficient storage and retrieval.

Required Qualifications

• Experience: 2+ years in data science
• Education: B tech, M tech in Computer Science, Statistics, Applied Mathematics, or related field
• Industry Knowledge: Preferred experience in Consumer Tech, Enterprise Tech, or Semiconductors but not mandatory

Technical Skills

• Programming:Proficiency inPython,SQLfor data analysis and transformation.
• Tools : Hands-on experience with Collibra Data Quality (CDQ)or similarData Quality tools(e.g., Informatica DQ, Talend, Great Expectations, Ataccama, etc.).
• Experience working withKubernetes workloads.
• Experience withAgile methodologiesand task tracking usingJira.

Preferred Skills

• Strong analytical and problem-solving skills with a results-oriented mindset.
• Good communication & requirement gathering capabilities.