AWS Data Engineer

Overview

We are seeking a talented and experienced AWS Data Engineer to join our data engineering team. The ideal candidate will have a strong background in building scalable data pipelines, designing data lake and data warehouse solutions, and leveraging AWS services for batch and streaming data processing. You will play a key role in transforming raw data into usable formats for analytics, business intelligence, and data science teams.

Key Responsibilities:

• Design, build, and maintain scalable ETL/ELT data pipelines on AWS using services like Glue, EMR, Lambda, Step Functions, and Kinesis.
• Develop and manage data lake architectures using S3, implementing bronze, silver, and gold layer models.
• Create and manage Glue Jobs, Glue Workflows, Crawlers, and integration with Glue Data Catalog.
• Implement batch and real-time data ingestion using Kafka, Kinesis, or Apache NiFi.
• Write efficient, scalable PySpark and Python code for data transformation and cleansing.
• Ensure data quality, profiling, validation, and compliance with governance standards.
• Collaborate with data scientists, analysts, and business stakeholders to deliver reliable and timely data.
• Monitor, troubleshoot, and optimize performance of data pipelines and workflows.
• Use Terraform, CloudFormation, or other IaC tools to manage AWS infrastructure.
• Implement logging, monitoring, and alerting with CloudWatch, SNS, and AWS Lambda.

Required Skills & Experience:

• 5+ years of experience as a Data Engineer, with 5+ years of hands-on experience in AWS data services.
• Strong expertise in AWS Glue, EMR, S3, Lambda, Kinesis, Redshift, Athena, and Step Functions.
• Proficient in Python, SQL, and PySpark for ETL development.
• Experience working with Apache Airflow, NiFi, or other workflow orchestration tools.
• Familiar with data modeling, data lakes, data warehousing, and data quality practices.
• Experience with containerization using Docker and orchestration using ECS/EKS.
• Strong understanding of IAM, KMS, VPC, and security best practices in AWS.
• Hands-on experience with version control systems (Git, GitHub, GitLab) and CI/CD tools (Jenkins, GitHub Actions, etc.).
• Experience with Databricks, Snowflake, or Redshift
• Familiar with Docker, Terraform, or Kubernetes

Preferred Qualifications:

• AWS Certifications such as AWS Certified Data Analytics, AWS Certified Solutions Architect – Associate, or Developer Associate.
• Familiarity with healthcare or financial data domains (HIPAA compliance a plus).

Job Type: Full-time

Schedule:

• Day shift

Application Question(s):

• What is your Total Experience?
• What is your Current Salary?
• What is your Expected Salary?
• Are you available to join immediately?
• What is your Current Location?

Experience:

• AWS Data Engineer: 5 years (Required)

Work Location: Remote