Location: Remote
Duration: Long-term contract
We are seeking a Senior Data Engineer with strong expertise in SQL, Python, Amazon Redshift, and AWS data technologies. The ideal candidate will have experience working with large-scale datasets, complex reporting systems, data quality validation, and performance optimization.
This role will focus on building data quality frameworks, troubleshooting data issues, creating automated validation processes, and supporting critical business reporting and analytics.
Must-have skills
- 10+ years of Data Engineering / Data Analytics experience
- Expert-level SQL (complex queries, joins, CTEs, window functions, optimization)
- Strong Python for data analysis and automation
- Extensive experience with Amazon Redshift
- Experience with materialized views and query performance tuning
- Experience handling large datasets and reporting platforms
- Strong knowledge of data validation, reconciliation, and data quality processes
- AWS experience with S3 and Glue
- Experience with Tableau and/or QuickSight
- Excellent communication and stakeholder collaboration skills
Preferred skills
- AWS Athena
- AWS Lambda
- SNS/SQS
- Apache Spark
- AI tools such as GitHub Copilot, Amazon Q, Claude, Google Cloud AI, or Tableau AI
- Agile/Scrum experience
Key responsibilities
- Write and optimize complex SQL queries for reporting and analytics
- Build automated data quality checks and validation frameworks
- Monitor data pipelines and investigate data issues
- Perform root cause analysis and remediation
- Optimize Redshift performance and materialized views
- Develop Python automation scripts for data validation
- Collaborate with architects, engineers, analysts, and business teams
- Document data quality rules, lineage, and validation processes
Technical stack
- SQL
- Python
- Amazon Redshift
- AWS S3
- AWS Glue
- Athena
- Tableau
- QuickSight
- Apache Spark
- Git
- CI/CD
GlobalPoint