Data Engineer II - Snowflake, Python

Centene Corporation is a diversified national organization focused on improving health outcomes through technology. They are seeking a Data Engineer II to develop and operationalize data pipelines, ensuring data availability for reports and advanced analytics while engaging with DevSecOps for continuous integration and deployment.

Responsibilities:

• Designs and implements standardized data management procedures around data staging, data ingestion, data preparation, data provisioning, and data destruction (scripts, programs, automation, assisted by automation, etc.)
• Designs, develops, implements, tests, documents, and operates large-scale, high-volume, high-performance data structures for business intelligence analytics
• Designs, develops, and maintains scheduled processes supporting automated daily, weekly and monthly refreshes
• Ensure quality of technical solutions as data moves across Centene’s environments
• Provides insight into the changing data environment, data processing, data storage, and utilization requirements for the company and offers suggestions for solutions
• Develops, constructs, tests, and maintains architectures using programming language and tools
• Identifies ways to improve data reliability, efficiency, and quality; use data to discover tasks that can be automated
• Performs other duties as assigned
• Complies with all policies and standards

Requirements:

• A Bachelor's degree in a quantitative or business field (e.g., statistics, mathematics, engineering, computer science)
• 2 – 4 years of related experience
• Experience with SQL and/or PL-SQL
• Teradata or Snowflake desired including experience developing intermediate to large data pipelines in Snowflake
• Hands on experience with Python or other languages
• Experience with Power BI or other data visualization tools
• Knowledge of CI/CD including automated deployments (Gitlab or other tools)
• Familiarity diagnosing system issues, data validation and quality assurance testing
• Implementation of common engineering best practices including documentation in project management tools such as JIRA
• Seeks to learn new technology and stay up to date with trends in data analysis and data engineering
• Ability to identify problems and procedural irregularities, collect data, establish facts, and draw conclusions
• Ability to work independently