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3 days ago
In this pivotal leadership position, you will spearhead the development of foundational components for a data lakehouse architecture on AWS and drive the migration of existing data processing workflows to the new solution.
- You will collaborate closely with the Data Engineering organization to design and implement scalable data infrastructure and processes using technologies such as Python, PySpark, EMR Serverless, Iceberg, Glue, and Glue Data Catalog.
The primary objective of this role is to ensure successful migration and establish robust data quality governance across the new platform, enabling reliable and efficient data processing.
Success in this position requires deep technical expertise, exceptional problem-solving skills, and the ability to lead and mentor within an agile team.
Mandatory Technical Skills:- Prior experience as a Principal Engineer, leading best practices in design, development, and implementation, mentoring team members, and fostering a culture of continuous learning and innovation.
- Extensive experience in software architecture and solution design, including microservices, distributed systems, and cloud-native architectures.
- Expertise in Python and Spark, with a focus on ETL data processing and data engineering practices.
- Deep knowledge of AWS data services and engineering practices, with demonstrable experience of implementing data pipelines using tools like EMR, AWS Glue, AWS Lambda, AWS Step Functions, API Gateway, Athena.
- Experience in delivering Lakehouse solutions/architectures.
- Knowledge of additional programming languages and development tools to provide flexibility and adaptability across varied data engineering projects.
- A master's degree or relevant certifications (e.g., AWS Certified Solutions Architect) is advantageous.
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