Note: The job is a remote job and is open to candidates in USA. HCLTech is seeking a Data Analyst Engineer with a strong focus on Data Quality and ETL/ELT Testing. The role involves driving data validation, quality governance, and testing strategies across large-scale AWS-based data platforms while collaborating with Data Engineers and Business Stakeholders to ensure data accuracy and reliability.
Responsibilities
- Validate ETL/ELT transformation logic against business requirements and specifications
- Perform source-to-target reconciliation to ensure data completeness and accuracy
- Identify data anomalies, schema drift, silent failures, and quality issues
- Design and maintain automated data validation frameworks and test suites
- Conduct periodic audits and quality assessments across data pipelines
- Define acceptance criteria and quality gates for ETL pipelines
- Create comprehensive test plans covering functional, integration, regression, and performance testing
- Establish Definition of Done (DoD) standards for production-ready data assets
- Implement release validation processes and defect management workflows
- Develop data quality SLAs for freshness, accuracy, and completeness
- Build dashboards and reporting solutions to track data quality metrics
- Configure monitoring and alerting for data quality threshold violations
- Measure and report on DQ scores, defect density, MTTR, and SLA compliance
- Lead continuous improvement initiatives and quality retrospectives
- Participate in data architecture and pipeline design reviews
- Work with business stakeholders to translate requirements into measurable test criteria
- Partner with Data Engineers to improve pipeline reliability and performance
- Support downstream teams in validating data used by applications and dashboards
Skills
- Advanced SQL (CTEs, Window Functions, Complex Joins, Data Profiling)
- AWS Data Services: Redshift, Athena, Lake Formation, S3 Data Lakes
- Python for automation, validation, and data testing frameworks
- Strong knowledge of ETL/ELT architectures and failure modes
- Test Planning, Defect Lifecycle Management, and QA Methodologies
- Data Profiling, Reconciliation, and Statistical Validation Techniques
- Experience with Great Expectations, dbt Tests, Soda Core, or similar frameworks
- Git / Version Control
- 6–10 years of experience in Data Engineering, Analytics Engineering, or Data QA
- Proven ownership of data quality strategy for production data platforms
- Experience defining release gates and preventing defective data deployments
- Hands-on experience building automated validation frameworks
- Ability to review and validate transformation logic and orchestration workflows
- Experience supporting data products that power business applications and reporting
- US Citizen or Green Card Holder Required (Due to program compliance requirements)
- BDD-style testing for data transformations
- CI/CD integration for automated data quality controls
- Experience defining Data SLAs and SLOs
- AWS Glue, Redshift Spectrum, Step Functions, or Airflow experience
- Data governance, IAM, and Lake Formation access controls
- Performance testing and pipeline observability
- Regulatory/compliance-driven data environments
Benefits
- Performance-based bonuses subject to company policies
- Medical, dental, vision, pharmacy, life, accidental death & dismemberment, and 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 per year
- Continuous opportunities for you to find your spark and grow with us
- Transparent communication with senior-level employees
- Learning and career development programs at every level
- Opportunities to experiment in different roles or even pivot industries
Company Overview