Python h1.location_city

Preferred Qualifications:
• Bachelor of Science degree in Computer Science or equivalent
• Vantage Master 2.0 certifications / Vantage Data Science Master certifications
• At least 7 years of post-degree professional experience
• At least 5+ years of Airline industry experience
• 4+ years development experience building and maintaining ETL pipelines
• 3+ years of experience working with database technologies and data development such as Python, PLSQL, etc.
• Experience in mentoring junior team members through code reviews and recommend adherence to best practices
• Deep understanding of writing test cases to ensure data quality, reliability and high level of confidence
• Track record of advancing new technologies to improve data quality and reliability
• Continuously improve quality, efficiency, and scalability of data pipelines
• Expert skills working with queries/applications, including performance tuning, utilizing indexes, and materialized views to improve query performance
• Identify necessary business rules for extracting data along with functional or technical risks related to data sources (e.g. data latency, frequency, etc.)
• Develop initial queries for profiling data, validating analysis, testing assumptions, driving data quality assessment specifications, and define a path to deployment
• Familiar with best practices for data ingestion and data design

Key Responsibilities and Skillets:
• Database Management, ETL Development, have used tools like Teradata Utilities (e.g., BTEQ, FastLoad, MultiLoad, TPT, etc.), Data Modeling, DB Performance Tuning, Data Security & Governance, Cloud Integration and Management, Cloud Infrastructure, Automation and DevOps, Data Warehousing and Analytics, Security and Compliance
• In-depth knowledge of Teradata architecture and components (e.g., AMP, Nodes, Parsing Engines, etc.).
• Proficiency in Teradata SQL and Teradata utilities.
• Strong SQL skills for querying and managing relational databases.
• Scripting experience (e.g., Shell, Python) for automating tasks.
• Knowledge of query optimization techniques, indexing, partitioning, and workload management in Teradata.
• Proficiency with core AWS services: EC2, S3, RDS, Lambda, CloudWatch, CloudFormation, etc.
• Familiarity with AWS storage options, such as S3, EFS, and Glacier, in the context of large-scale data storage and retrieval.
• Knowledge of AWS services that enhance Teradata performance, such as using S3 for staging data or integrating with Redshift for analytics.
• Hands-on experience with AWS CloudFormation, Terraform, or similar tools for automating infrastructure deployment.
• Proficiency in automating ETL pipelines and data processing workflows using AWS Lambda, Step Functions, or AWS Glue