What are the responsibilities and job description for the Lead Data Engineer AWS position at Jobs via Dice?
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Job Summary:
We are seeking a highly skilled Lead Data Engineer with deep expertise in AWS cloud services to design, build, and optimize scalable data platforms. This role involves leading data engineering initiatives, architecting robust ETL pipelines, and collaborating with cross-functional teams to deliver secure, high-performance data solutions.
Key Responsibilities:
Job Summary:
We are seeking a highly skilled Lead Data Engineer with deep expertise in AWS cloud services to design, build, and optimize scalable data platforms. This role involves leading data engineering initiatives, architecting robust ETL pipelines, and collaborating with cross-functional teams to deliver secure, high-performance data solutions.
Key Responsibilities:
- Architect and Develop Data Solutions: Design and implement large-scale data pipelines and data lakes using AWS services such as Glue, Redshift, S3, Lambda, EMR, Kinesis, and Athena.
- Data Modeling & Warehousing: Build and optimize data models for analytics and reporting using Redshift and other AWS-native tools.
- ETL Development: Develop and maintain ETL workflows leveraging AWS Glue, Step Functions, and Python.
- Performance Optimization: Ensure data systems are highly available, secure, and optimized for performance and cost efficiency.
- Automation & Infrastructure as Code: Implement automation using Terraform or CloudFormation for provisioning and managing AWS resources.
- Data Governance & Security: Enforce data privacy, compliance, and security standards (e.g., IAM roles, encryption, GDPR).
- Leadership & Mentorship: Lead a team of data engineers, provide technical guidance, and establish best practices for data engineering.
- Collaboration: Work closely with data scientists, analysts, and business stakeholders to deliver data-driven solutions.
- Experience: 8 years in data engineering, with at least 3 years in AWS-based solutions.
- Technical Expertise:
- AWS services: Glue, Redshift, S3, Lambda, EMR, Kinesis, Athena
- Programming: Python, SQL
- ETL tools and frameworks
- Data modeling and warehousing concepts
- Tools & Frameworks:
- CI/CD pipelines (Jenkins, CodePipeline)
- Infrastructure as Code (Terraform, CloudFormation)
- Monitoring tools (CloudWatch)
- Certifications (Preferred): AWS Certified Data Analytics Specialty or AWS Solutions Architect Professional.
- Soft Skills: Strong leadership, communication, and problem-solving abilities.