Overview

Our client, a rapidly expanding global technology partner, is looking for a highly skilled Senior Python Data Engineer to join their exceptional Technology and Development team.

Responsibilities

• ETL Pipeline Development: Design, develop, and maintain ETL processes using Python, AWS Glue, or other serverless technologies to ingest data from various sources (databases, APIs, files), transform it into a usable format, and load it into data warehouses or data lakes.
• AWS Serverless Expertise: Leverage AWS services such as AWS Lambda, AWS Step Functions, AWS Glue, AWS S3, and AWS Redshift to build serverless data pipelines that are scalable, reliable, and cost-effective.
• Data Modeling: Collaborate with data scientists and analysts to understand data requirements and design appropriate data models, ensuring data is structured optimally for analytical purposes.
• Data Quality Assurance: Implement data validation and quality checks within ETL pipelines to ensure data accuracy, completeness, and consistency.
• Performance Optimization: Continuously optimize ETL processes for efficiency, performance, and scalability, monitoring and troubleshooting any bottlenecks or issues that may arise.
• Documentation: Maintain comprehensive documentation of ETL processes, data lineage, and system architecture to ensure knowledge sharing and compliance with best practices.
• Security and Compliance: Implement data security measures, encryption, and compliance standards (e.g., GDPR, HIPAA) as required for sensitive data handling.
• Monitoring and Logging: Set up monitoring, alerting, and logging systems to proactively identify and resolve data pipeline issues.
• Collaboration: Work closely with cross-functional teams, including data scientists, data analysts, software engineers, and business stakeholders, to understand data requirements and deliver solutions.
• Continuous Learning: Stay current with industry trends, emerging technologies, and best practices in data engineering and cloud computing and apply them to enhance existing processes.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Proven experience as a Data Engineer with a focus on ETL pipeline development.
• Strong proficiency in Python programming.
• In-depth knowledge of AWS serverless technologies and services.
• Familiarity with data warehousing concepts and tools (e.g., Redshift, Snowflake).
• Strong SQL skills for data extraction and transformation.
• Excellent problem-solving and troubleshooting abilities.
• Ability to work independently and collaboratively in a team environment.
• Effective communication skills for articulating technical concepts to non-technical stakeholders.
• Certifications such as AWS Certified Data Analytics - Specialty or AWS Certified DevOps Engineer are a plus.
• Preferred Experience: .