Senior Developer, Data Eng

What you'll do

• Design, develop, and maintain end-to-end batch and near real-time data pipelines using Snowflake, AWS, and Python.
• Build and optimize data models in Snowflake, including dimensional modeling and curated data marts.
• Develop and maintain ETL/ELT workflows using Python and IBM DataStage while migrating legacy workloads.
• Implement job scheduling, monitoring, and operational support using Control-M for alerting and dependency management.
• Ensure data quality, governance, lineage, and documentation standards are met across all pipelines.
• Perform performance tuning and cost optimization for Snowflake and AWS resources.
• Troubleshoot production issues, perform root-cause analysis, and drive preventative improvements.
• Partner with stakeholders to enable data products and AI-ready datasets for Data Science and BI teams.

What we're looking for

• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
• 9+ years of data engineering experience, including enterprise-grade data platform delivery and production support.
• 3+ years of experience in a data engineering capacity.
• Strong expertise in Snowflake architecture, SQL development, performance tuning, security, and data loading.
• Hands-on experience with AWS data ecosystem services such as S3, IAM, Glue, Lambda, and EMR.
• Strong Python programming skills for ETL/ELT frameworks, API ingestion, automation, and unit testing.
• Experience designing and managing enterprise job scheduling, dependencies, and SLAs using Control-M.
• Experience with Git and CI/CD practices for data pipelines (preferred).
• Experience with IBM DataStage for building and maintaining jobs (preferred).
• Experience enabling AI/ML pipelines or familiarity with MLOps tools (preferred).