Job Overview
We are seeking a highly skilled Senior Data Engineer to design build and scale modern data platforms that power analytics and machine learning initiatives. This role focuses on developing cloud-native data solutions ensuring high-performance data pipelines and enabling data-driven decision-making across complex environments.
Key Responsibilities
- Design and implement end-to-end data architectures across ingestion storage processing orchestration and serving layers on AWS
- Build and maintain scalable ETL/ELT pipelines for multi-source data ingestion
- Develop and manage feature stores to support advanced analytics and machine learning use cases
- Collaborate with ML and analytics teams to productionize data and ML workflows
- Monitor and optimize data platform performance reliability and scalability
- Ensure best practices in data quality governance and security
Technical Requirements
- 5 years of experience in data engineering building complex data pipelines and architectures
- Strong expertise in Python (Pandas NumPy) for data processing
- Advanced proficiency in SQL and relational databases
- Hands-on experience with AWS data services and serverless architecture
- Solid experience working in Linux environments and Bash scripting
- Strong understanding of data governance privacy and quality frameworks
Nice to Have
- Experience working with IoT data pipelines and streaming data systems
Job Overview We are seeking a highly skilled Senior Data Engineer to design build and scale modern data platforms that power analytics and machine learning initiatives. This role focuses on developing cloud-native data solutions ensuring high-performance data pipelines and enabling data-driven decis...
Job Overview
We are seeking a highly skilled Senior Data Engineer to design build and scale modern data platforms that power analytics and machine learning initiatives. This role focuses on developing cloud-native data solutions ensuring high-performance data pipelines and enabling data-driven decision-making across complex environments.
Key Responsibilities
- Design and implement end-to-end data architectures across ingestion storage processing orchestration and serving layers on AWS
- Build and maintain scalable ETL/ELT pipelines for multi-source data ingestion
- Develop and manage feature stores to support advanced analytics and machine learning use cases
- Collaborate with ML and analytics teams to productionize data and ML workflows
- Monitor and optimize data platform performance reliability and scalability
- Ensure best practices in data quality governance and security
Technical Requirements
- 5 years of experience in data engineering building complex data pipelines and architectures
- Strong expertise in Python (Pandas NumPy) for data processing
- Advanced proficiency in SQL and relational databases
- Hands-on experience with AWS data services and serverless architecture
- Solid experience working in Linux environments and Bash scripting
- Strong understanding of data governance privacy and quality frameworks
Nice to Have
- Experience working with IoT data pipelines and streaming data systems
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