AWS Data Quality Engineer

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

AWS Data Quality Engineer (ITAR/EAR Compliant Role)

Experience: 2–3 Years

Location: United States (Remote/Hybrid)

Important: This position supports programs subject to U.S. export control regulations (ITAR/EAR). Candidates must be U.S. Citizens, U.S. Permanent Residents (Green Card Holders), or otherwise authorized to access export-controlled information under applicable U.S. regulations.

We are seeking a highly motivated AWS Data Quality Engineer to join our growing Data Engineering and Analytics team. In this role, you will be responsible for ensuring the accuracy, completeness, consistency, and reliability of data across enterprise data platforms. You will design and implement automated data validation frameworks, monitor data quality metrics, and proactively identify data anomalies across AWS-based data ecosystems.

The ideal candidate will have hands-on experience with AWS data services, Python automation, SQL, and data quality frameworks, with a strong passion for building scalable testing solutions that support modern DataOps and Analytics initiatives.

Key Responsibilities

Data Quality Automation

• Develop automated validation frameworks to verify source-to-target data movement across enterprise data pipelines.
• Create reusable Python-based testing utilities and automation scripts for validating schema consistency, completeness, accuracy, and timeliness of datasets.
• Design and maintain data reconciliation processes for large-scale structured and semi-structured datasets.
• Validate data pipelines built on AWS services including Amazon S3, AWS Glue, Amazon Redshift, and AWS Lambda.
• Perform end-to-end testing of ETL/ELT workflows and cloud-native data architectures.
• Ensure data transformation logic and business rules are correctly implemented throughout the data lifecycle.

Data Monitoring & Observability

• Implement continuous monitoring solutions for:
• Schema validation
• Data anomaly identification
• Build and maintain data quality dashboards, alerts, and operational reports.
• Establish proactive controls to detect and prevent data quality issues before they impact business stakeholders.

Collaboration & Business Alignment

• Partner with Data Engineers, BI Developers, Data Analysts, and Application Teams to translate business requirements into measurable data quality KPIs and SLAs.
• Participate in DataOps processes and CI/CD deployments to ensure quality checks are integrated into delivery pipelines.
• Support root-cause analysis and remediation of data quality issues.

Performance & Optimization

• Analyze large-scale datasets using SQL and Python to identify inconsistencies and trends.
• Optimize validation frameworks for scalability and performance.
• Contribute to data governance and quality best practices across the organization.

Required Qualifications

Experience

• 2–3 years of experience in Data Engineering, Data Quality Engineering, ETL Testing, or related roles.
• Experience working with enterprise-scale cloud data platforms.

Technical Skills

AWS

Strong hands-on experience with:

• Amazon S3
• AWS Glue
• Amazon Redshift
• AWS Lambda
• CloudWatch (preferred)
• EventBridge/Step Functions (good to have)

Programming & Automation

• Advanced proficiency in Python.
• Experience building automation frameworks and validation utilities.
• Experience with Pandas, PySpark, or equivalent data processing libraries.

Data Quality & Testing

• Experience implementing data quality monitoring frameworks such as:
• Amazon Deequ
• Custom Python-based validation frameworks
• Knowledge of data profiling, reconciliation, and quality assurance methodologies.
• Experience with Apache Airflow or similar orchestration tools.
• Understanding of ETL/ELT architectures and data transformation processes.
• Experience working with batch and distributed data processing environments.

Database & Scripting

• Strong SQL skills for data validation and analysis.
• Experience with UNIX/Linux shell scripting.
• Understanding of data warehousing concepts and dimensional modeling.

Preferred Qualifications

• AWS Certified Data Engineer – Associate (Highly Preferred).
• Experience with DataOps/DevOps practices.
• Knowledge of CI/CD pipelines and automated testing integration.
• Experience with data observability platforms and monitoring solutions.
• Exposure to Agile/Scrum delivery environments.

Soft Skills

• Excellent analytical and problem‑solving capabilities.
• Strong communication and stakeholder management skills.
• Ability to work independently in a fast‑paced environment.
• Strong attention to detail and commitment to data accuracy.

Why Join Us?

• Work on cutting‑edge cloud data platforms and analytics initiatives.
• Opportunity to build enterprise‑scale data quality frameworks from the ground up.
• Collaborate with highly skilled Data Engineering and Analytics teams.
• Grow your AWS and DataOps expertise while solving complex data challenges.

Pay and Benefits

Pay Range Minimum: $ 59000 per year

Pay Range Maximum: $ 99000 per year

HCLTech is an equal opportunity employer, committed to providing equal employment opportunities to all applicants and employees regardless of race, religion, sex, color, age, national origin, pregnancy, sexual orientation, physical disability or genetic information, military or veteran status, or any other protected classification, in accordance with federal, state, and/or local law. Should any applicant have concerns about discrimination in the hiring process, they should provide a detailed report of those concerns to [e-mail] for investigat

ion.A candidate’s pay within the range will depend on their skills, experience, education, and other factors permitted by law. This role may also be eligible for performance‑based bonuses subject to company policies. In addition, this role is eligible for the following benefits subject to company policies:

• medical
• dental
• vision
• pharmacy
• life
• accidental death & dismemberment
• disability insurance
• employee assistance program
• 401(k) retirement plan
• 10 days of paid time off per year (some positions are eligible for need‑based leave with no designated number of leave days per year)
• 10 paid holidays peryear

How You’llGrow

At HCLTech, we offer continuous opportunities for you to find your spark and grow with us. We want you to be happy and satisfied with your role and to really learn what type of work sparks your brilliance the best. Throughout your time with us, we offer transparent communication with senior‑level employees, learning and career development programs at every level, and opportunities to experiment in different roles or even pivot industries. We believe that you should be in control of your career with unlimited opportunities to find the role that fits you best.