Remote Data Quality Engineer - AWS | Python & DataOps

HCLTech; Seattle (WA); On-site; USD 78,000 - 148,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) retirement plan

PTO 10 days

Job summary

HCLTech is seeking a Data Quality Engineer to advance data quality across the data pipeline in the US market. You will develop automated data validations, leverage AWS Glue, Redshift, S3, Lambda, and Airflow, and apply Deequ to monitor quality KPIs.

The role requires strong Python, SQL, and UNIX/Linux scripting, collaboration with data engineers and BI teams, and the ability to translate business rules into data quality metrics. Remote-friendly with competitive pay and benefits.

Qualifications

• Deep proficiency in AWS data services (S3, Glue, Redshift, Lambda).
• Advanced Python for automation and tests.
• Experience with Airflow, data transformation, and Deequ.

Responsibilities

• Develop automated scripts to validate source-to-target data movements and ensure schema consistency.
• Build reusable testing utilities integrating into DataOps workflows.
• Set up data drift monitoring, schema validation, and quality dashboards.
• Collaborate with data engineers, BI teams, and software engineers to translate business rules into data quality KPIs and SLAs.

Skills

Python

SQL

UNIX/Linux scripting

Apache Airflow

Tools

AWS Glue

Amazon Redshift

AWS Lambda

Amazon S3

Amazon Deequ

Job description

HCLTech is seeking a Data Quality Engineer to advance data quality across the data pipeline in the US market. You will develop automated data validations, leverage AWS Glue, Redshift, S3, Lambda, and Airflow, and apply Deequ to monitor quality KPIs.

The role requires strong Python, SQL, and UNIX/Linux scripting, collaboration with data engineers and BI teams, and the ability to translate business rules into data quality metrics. Remote-friendly with competitive pay and benefits.