Data Engineer - AWS

Key Responsibilities

• 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 technologies.
• Migrate data from traditional relational databases, file systems, and APIs to AWS-based data lakes (S3), RDS, Aurora, and Redshift.
• Implement high-velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred).
• Architect and implement CI/CD strategies for enterprise data platforms.
• Collaborate with product, operations, QA, and cross-functional teams throughout the software development cycle.
• Stay abreast of new technology developments, implement POCs for new tools/technologies, and onboard them for real-world use cases.
• Identify and resolve performance issues and continuously optimize for cost, reliability, and scalability.

Required Qualifications

• 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 technologies.
• Familiarity with data warehousing concepts and cloud-based architecture.
• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork abilities.

Preferred Qualifications

• Experience with additional AWS services: API Gateway, ElasticSearch, SQS.
• Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation).
• Experience with DevOps practices and CI/CD pipelines.
• Experience implementing end-to-end streaming solutions (Amazon Kinesis, SQS, Kafka).
• AWS Solutions Architect or AWS Developer Certification preferred.
• Understanding of Lakehouse/data cloud architecture.
• Knowledge of data governance and compliance standards.

Pay rate: $60 - $70 per hour, depending on experience.