Data Lake Architect Lead
1 week ago
About Amicon Hub Services
We are a leading provider of innovative data modernization, analytics and AI solutions. Our team specializes in leveraging cutting-edge technologies to help businesses build and manage scalable data lakes and data lakehouses.
Job Description
This role involves designing, implementing, and optimizing our next-generation data lake architecture. You will lead the development of scalable data platforms using Apache Spark and modern table formats like Apache Iceberg.
We are looking for a Data Lake Architect Lead to join our team.
Key ResponsibilitiesData Lake Architecture:
- Design and implement modern data lake architectures using best practices for data organization, partitioning, and storage optimization.
Spark Development:
- Lead the development of data processing applications using PySpark, optimizing for performance and resource utilization across large-scale Spark clusters.
Table Format Implementation:
- Design and implement data storage strategies using Apache Iceberg, enabling ACID transactions, time travel, and schema evolution capabilities.
Data Pipeline Development:
- Create robust and scalable data pipelines for batch and streaming workflows, implementing proper error handling and data quality checks.
Performance Optimization:
- Tune Spark applications and cluster configurations for optimal performance, implementing partitioning strategies and query optimization techniques.
Data Governance:
- Establish and maintain data governance frameworks specific to data lake environments, including access controls, audit logging, and compliance measures.
Infrastructure as Code:
- Develop and maintain infrastructure as code for automated deployment of data lake components and Spark clusters.
Cross-functional Leadership:
- Collaborate with data engineers, data scientists, and business stakeholders to ensure the data lake architecture meets both technical and business requirements.
You will need to have:
- Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
- 12+ years of experience in data engineering, with at least 3 years focused on data lake architecture and implementations.
- Deep expertise in Apache Spark and PySpark, including complex ETL development, performance tuning and optimization, Spark SQL and DataFrame APIs, Spark cluster management and monitoring.
- Strong experience with Apache Iceberg, including table management and optimization, schema evolution, time travel operations, and partition evolution.
- Proficiency in Python programming and software engineering best practices.
- Experience with cloud platforms (AWS, Azure, or GCP) and their respective data lake services.
- Strong understanding of data modeling concepts for both structured and unstructured data.
- Experience with version control systems (Git) and CI/CD pipelines.
The estimated salary for this role is around $175,000 per year, depending on location and qualifications.
We offer a comprehensive benefits package, including health insurance, professional development support, and a remote-friendly work environment with flexible scheduling options.
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