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Senior Data Engineer, Strategic Partnerships - Amazon
Data Engineer
Senior Data Engineer driving data pipelines and analytics for high‑impact strategic partnership initiatives, leveraging Python, Spark, SQL, and AWS services to deliver scalable, reliable data solutions.
About the role
Key Responsibilities
- Design, build, and maintain robust data pipelines that ingest, transform, and store partnership‑related data across multiple AWS services.
- Develop scalable ETL processes using Python, Apache Spark, and Airflow to support analytics, reporting, and decision‑making for strategic initiatives.
- Collaborate with product, finance, and business development stakeholders to translate partnership requirements into data models and actionable insights.
- Implement data quality, monitoring, and governance frameworks to ensure accuracy and reliability of critical partnership metrics.
- Optimize performance and cost of data workloads on AWS (e.g., Redshift, S3, Glue, Lambda) and continuously improve architecture for scalability.
Requirements
- 5+ years of professional experience building large‑scale data pipelines and analytics solutions.
- Strong proficiency in Python, SQL, and Apache Spark for data processing.
- Hands‑on experience with AWS data services such as Redshift, S3, Glue, Lambda, and orchestration tools like Airflow.
- Solid understanding of data modeling, ETL best practices, and data warehousing concepts.
- Excellent problem‑solving skills and ability to work cross‑functionally with senior stakeholders in a fast‑paced environment.
Skills
pythonsqlapache sparkawsairflow