The AWS Data Engineer – Qualtrics Integration is responsible for designing, building, and maintaining scalable, automated data pipelines that support Qualtrics survey ingestion, transformation, and downstream reporting. This role focuses on serverless AWS data engineering, integrating Qualtrics APIs with AWS services to process structured survey data, dealer hierarchies, and reporting files. The engineer will ensure data accuracy, automation, monitoring, and performance across end-to-end workflows.
Key Responsibilities AWS Cloud & Data Engineering
Design and maintain ETL pipelines using AWS Glue (PySpark)
Develop AWS Lambda functions (Python / Node.js) for serverless data processing
Manage AWS S3 for Qualtrics input/output storage and optimized data access
Orchestrate workflows using AWS Step Functions and MWAA (Airflow)
Query structured datasets using AWS Athena
Monitor pipelines using CloudWatch logs and metrics
Data Processing & ETL
Transform and aggregate Qualtrics datasets (CSV, JSON, XML)
Connect AWS pipelines with CRM, ERP, BI tools, or downstream platforms
Data Quality & Reporting
Perform data validation and quality checks prior to Qualtrics ingestion
Generate formatted output files aligned to business-defined templates
Support ad-hoc analysis using SQL and Athena
Programming & Automation
Develop robust Python scripts for Glue, Lambda, and automation tasks
Write optimized SQL queries for structured data access
Use Bash/Shell scripting for file movement and preparation
DevOps & Security (Nice to Have)
Configure IAM roles and permissions securely
Implement Infrastructure as Code (Terraform / CloudFormation)
Support CI/CD pipelines for data workflows
Required Skills & Experience
Strong experience in AWS Data Engineering & Serverless Architecture
Hands-on expertise with AWS Glue, Lambda, S3, Athena, Step Functions
Experience with MWAA (Airflow) for orchestration
Strong Python and SQL skills
Experience integrating Qualtrics API or structured survey data
Ability to troubleshoot pipeline failures and performance issues
Preferred / Nice-to-Have Skills
Experience with Terraform or CloudFormation
CI/CD for data pipelines
Experience supporting BI tools (Power BI, Tableau, etc.)
Knowledge of data governance and security best practices
Ideal Candidate Profile
AWS-focused Data Engineer with strong automation mindset
Comfortable working with survey / VoC / structured data
Strong debugging, monitoring, and optimization skills
Able to work independently in enterprise environments
Recruiter Submission Template –
Full Name: Degree Major with University & Completion Year: Total Years of Data Engineering Experience: Total Years of AWS Data Engineering Experience:
Total Years of Experience with Serverless Architecture: Experience with AWS Glue (PySpark ETL)? (Yes/No – please elaborate): Experience with AWS Lambda (Python/Node.js)? (Yes/No – please elaborate):
Experience with AWS S3 data storage & optimization?
Experience with AWS Athena? (Yes/No):
Experience implementing data validation & quality checks? Experience working with Qualtrics API? (Yes/No – please specify): Experience with event-driven processing (S3 → Lambda)? Experience integrating AWS with CRM / ERP / BI tools? Python Experience (years & libraries used): SQL Experience (years & databases/tools):
Experience with IAM & role-based access?
Brief description of a recent AWS data pipeline you built (tools + outcome):
Motivation / Reason for Interest in Qualtrics Data Engineering Role: Contact Number: Email ID:
LinkedIn Profile URL:
Full Address (Street, City, State, Zip):
Notice Period (in weeks):
Current Work Authorization Status:
Expected Hourly Rate:
W2 / C2C (If C2C, corporation name): Are you comfortable working primarily Remote with Limited Onsite Flexibility?
