Data Scientist II

Role Overview

Are you excited about Data Assets and the value they brings to an organization? Are you an evangelist for data driven decision making? Are you motivated to be part of a Global Analytics team that builds large scale Analytical Capabilities supporting end users across 6 continents? Do you want to be the go-to resource for data analytics in the company?

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines supporting enterprise data and analytics initiatives.
• Build and optimize batch and real-time data processing solutions using SQL, Python, Spark, and related technologies.
• Ensure data availability, accuracy, consistency, and reliability across data platforms and pipelines.
• Implement data quality controls, testing frameworks, monitoring, and observability practices to support trusted data products.
• Apply engineering best practices including version control, CI/CD, DataOps, and automated deployment methodologies.
• Support platform upgrades, migrations, operational maintenance, and ongoing production support activities.
• Collaborate with Data Engineers, Data Scientists, Analysts, and business stakeholders to translate business requirements into scalable data solutions.
• Participate in technical design reviews, code reviews, and architecture discussions to drive engineering excellence.
• Create and maintain technical documentation, standards, and operational procedures.

Requirements

• Hands-on experience in data engineering, data integration, and large-scale data processing.
• Strong proficiency in SQL and Python for data transformation, automation, and analytics workloads.
• Solid understanding of data modeling, database design, and performance optimization techniques.
• Experience designing and developing ETL/ELT solutions across modern data platforms.
• Knowledge of data quality frameworks, testing methodologies, and data validation practices.
• Familiarity with cloud-based or modern enterprise data platforms.
• Experience with source control, CI/CD pipelines, and software engineering best practices.
• Strong analytical and problem-solving skills with the ability to troubleshoot complex data issues.
• Excellent communication and collaboration skills with the ability to work effectively across technical and business teams.
• Self-motivated, detail-oriented, and committed to delivering high-quality, scalable solutions.

Nice to Have

• Experience with PySpark and Apache Spark for distributed data processing.
• Experience working within the Hadoop ecosystem and large-scale data environments.
• Familiarity with GitLab, Jenkins, or similar DevOps and CI/CD platforms.
• Exposure to Power BI or other business intelligence and data visualization tools.
• Understanding of modern data architecture patterns supporting analytics, machine learning, and AI workloads.

Skills

• SQL
• Python
• Spark
• PySpark
• Hadoop