Remote AWS Data Quality Engineer — DataOps & Validation

HCLTech; United States; Hybrid; USD 59,000 - 99,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

401(k) retirement plan

Paid time off

Job summary

HCLTech is seeking an AWS Data Quality Engineer to ensure accuracy and reliability of data across enterprise platforms. You will design automated validation frameworks, monitor quality metrics, and address anomalies within AWS-based data ecosystems.

The role emphasizes hands-on AWS services, Python automation, SQL, and DataOps practices to support scalable testing and analytics initiatives across remote and hybrid US environments.

Qualifications

• 2–3 years of experience in Data Engineering, Data Quality Engineering, ETL Testing, or related roles.
• Experience with enterprise-scale cloud data platforms (AWS).
• Proficiency in Python and SQL for data validation and automation.
• Familiarity with data quality frameworks and data monitoring concepts.

Responsibilities

• Develop automated validation frameworks to verify data movement across pipelines.
• Create Python-based testing utilities for schema validation and data quality checks.
• Design and maintain data reconciliation processes for large datasets.
• Validate pipelines on AWS services like S3, Glue, Redshift, and Lambda.
• Implement data quality dashboards, alerts, and monitoring reports.

Skills

AWS

Python

SQL

Data Quality

ETL Testing

Pandas

PySpark

Airflow

Unix/Linux

Tools

AWS Glue

S3

Redshift

Lambda

CloudWatch

EventBridge/Step Functions

Job description

HCLTech is seeking an AWS Data Quality Engineer to ensure accuracy and reliability of data across enterprise platforms. You will design automated validation frameworks, monitor quality metrics, and address anomalies within AWS-based data ecosystems.

The role emphasizes hands-on AWS services, Python automation, SQL, and DataOps practices to support scalable testing and analytics initiatives across remote and hybrid US environments.