Lead Data Engineer

Job summary

Job Description: Lead Data Engineers (AWS) We are seeking a talented AWS Data Engineer to join our dynamic Data Engineering team. The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines and architectures in the AWS cloud environment.

Benefits

Qualifications

• the lower end applies to those with less experience or fewer preferred
• For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.
• Required
• Bachelor’s degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience.
• 5+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises.
• Strong programming experience with Python, Shell scripting, and SQL.
• Solid experience with AWS services: CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, Secrets Manager.
• Experience in serverless application development and data pipeline orchestration.
• Experience in system analysis, design, development, and implementation of data ingestion pipelines in AWS.
• Knowledge of ETL/ELT, data modeling, and big data
• Experience with additional AWS services: API Gateway, ElasticSearch, SQS.
• Experience with infrastructure-as-code

Responsibilities

• The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines and architectures in the AWS cloud environment.
• of the position.
• The top of the range is reserved for candidates who notably exceed the
• Design, build, and maintain efficient, reusable, and reliable architecture and code for data pipelines and data applications on AWS.
• Build robust data ingestion pipelines (from on-prem to AWS and within AWS) using AWS services such as Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, and SQS.
• Develop and manage ETL/ELT processes to collect, process, and store data from multiple sources, ensuring data quality, integrity, and security.
• Architect and implement end-to-end data solutions (ingestion, storage, integration, processing, access) on AWS, with a focus on data lakes and data warehouses.
• Participate in the architecture and system design discussions for high-scale data engineering projects.
• Independently perform hands-on development, unit testing, and participate in code reviews to ensure adherence to best practices.
• Implement serverless applications using AWS Lambda, API Gateway, Step Functions, and other AWS

Skills

Degrees

Industry

Company size

Security clearance