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aws sql python kubernetes dbt📋 Description
- Architect foundational data platform powering analytics and data products.
- Set data modeling, orchestration, testing, and observability standards.
- Build and optimize AWS data infrastructure (storage, compute, networking, security).
- Collaborate with Product/Analytics/Engineering to translate needs into data solutions.
- Drive performance, cost optimization, and data quality decisions.
- Mentor data engineers; own critical systems end-to-end and roadmap; ensure operational efficiency.
🎯 Requirements
- 7+ years in data/platform engineering; Spark, Python, SQL in production.
- Design/operate large-scale data systems on AWS.
- Deep data modeling, distributed systems, and performance tuning.
- Lead technical initiatives and influence architecture across teams.
- Comfortable in ambiguous, early-stage environments.
- Nice-to-have: Trino, dbt; lakehouse concepts; Kubernetes/EKS; Spark/Kafka.
🎁 Benefits
- Equal opportunity employer; inclusive culture.
- Reasonable accommodations for qualified applicants.
- Background checks completed in compliance with laws.
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