Description

Lead the design, development, and optimization of large-scale data pipelines and data lake architecture on AWS.

This role is hybrid.

Responsibilities

• Architect and implement end-to-end data solutions including ingestion, storage, transformation, and analytics using AWS services.
• Mentor and guide a team of data engineers, conducting code reviews and fostering best practices in cloud architecture.
• Oversee migration of data from legacy systems to AWS-based data lakes and warehouses.
• Drive adoption of DevOps, CI/CD, and infrastructure-as-code practices within the data engineering team.
• Develop and enforce standards for data quality, security, and governance.

Required Skills

• 7+ years of experience in data engineering, with at least 3 years in a technical leadership role.
• Extensive hands-on experience with AWS data services: Glue, Redshift, S3, Lambda, EMR, Kinesis, Athena, RDS.
• Proficiency in Python and SQL; experience with Shell scripting and Scala is a plus.
• Strong experience designing data lakes, data warehouses, and ETL/ELT processes.
• Experience with DevOps practices, CI/CD pipelines, and infrastructure-as-code tools like CloudFormation and Terraform.
• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Proven ability to lead, mentor, and coach engineers in a collaborative environment.

Preferred Skills

• AWS Solutions Architect or AWS Data Engineer certification.
• Experience with real-time streaming technologies and Lakehouse architecture.

Key Skills

Education

Bachelor's degree