Python Data Engineer

Tasks

• Develop, maintain, and optimize ETL pipelines and data workflows using schema-driven and configuration-driven approaches.
• Build and maintain hierarchical and dimensional data models that support analytics and reporting.
• Use AWS data services to securely store, manage, and process large datasets.
• Perform rigorous data validation and quality checks to maintain data accuracy, consistency, and integrity.
• Collaborate with cross-functional teams to integrate SQL queries and Databricks JDBC data feeds.
• Work with columnar

Requirements

• Hiring H1 and local H4 ead
• Strong proficiency in Python, including pandas and NumPy, with experience designing schema-driven and configuration-driven ETL pipelines.
• Experience designing hierarchical and dimensional data structures.
• Hands-on experience with Amazon S3, IAM, DynamoDB, and AWS Systems Manager Parameter Store (SSM).
• Expertise in data validation, quality engineering, testing, and reproducible data-code practices.
• Proficiency in SQL and experience working with Databricks JDBC feeds.
• Knowledge of columnar and analytical file formats, including Parquet and CSV, and their practical application.
• Experience handling and processing time-series datasets.
• Familiarity with Git, GitHub Actions, and Terraform for version control, automation, and infrastructure as code.
• Interface-level integration experience with Amazon SageMaker and Chronos endpoints.
• Strong understanding of secure data-handling practices across the data lifecycle.

Location

• Dallas, TX