What are the responsibilities and job description for the Data Quality Engineer (AWS, Airflow, DBT - Max $70/hr W2 ) position at Lenmar Consulting Inc?
Company Description
Education
Job Description
USC and GC only (No H1B, OPT, CPT at this time)
Data Quality Engineer (AWS Data Platform) Overview We are seeking a highly skilled Data Engineering - Quality Engineer to define and implement end-to-end testing strategies for a modern data platform built on AWS. This role will be responsible for ensuring data quality, reliability, and performance across the entire pipeline; from ingestion to transformation and reporting.
Key Responsibilities
All your information will be kept confidential according to EEO guidelines.
Education
Job Description
USC and GC only (No H1B, OPT, CPT at this time)
Data Quality Engineer (AWS Data Platform) Overview We are seeking a highly skilled Data Engineering - Quality Engineer to define and implement end-to-end testing strategies for a modern data platform built on AWS. This role will be responsible for ensuring data quality, reliability, and performance across the entire pipeline; from ingestion to transformation and reporting.
Key Responsibilities
- Define the end-to-end testing scope based on solution architecture and project documentation
- Design and implement a comprehensive testing strategy and plan aligned with organizational QA standards
- Develop and maintain test scripts and frameworks for the Redshift serverless platform
- Perform testing across key technologies, including:
- AWS Redshift
- AWS DMS (Data Migration Service)
- AWS Glue
- PySpark Deequ
- Event Bridge
- Data Lakes
- Python-based data pipelines
- Apache Airflow
- dbt (data build tool)
- Build and implement automated testing solutions to ensure:
- End-to-end data validation
- Data ingestion accuracy
- Transformation logic integrity
- Data pipeline reliability
- Conduct test coverage analysis and ensure adequate validation across all data engineering workflows
- Prepare and manage test data
- Review and provide feedback on:
- Solution architecture
- Data models
- Design and technical documentation
- Collaborate with cross-functional teams (Data Engineering, BI, DevOps, Product) to:
- Identify testing impacts
- Mitigate risks
- Ensure high-quality deliverables
- Proven experience in data engineering testing / data QA / ETL validation
- Strong hands-on experience with AWS data services (Redshift, Glue, DMS)
- Proficiency in Python for test automation and validation
- Experience with Airflow and orchestration testing
- Hands-on experience with dbt and data transformation validation
- Familiarity with CDK for infrastructure validation
- Experience in BI testing in Quicksuite will be highly beneficial
- Experience with data quality tools such as PySpark Deequ or similar
- Strong understanding of: Data warehousing concepts, ETL/ELT pipelines. Data validation techniques (schema, reconciliation, anomaly detection)
- Experience designing enterprise-level test strategies for data platforms
- Knowledge of CI/CD pipelines for data and test automation
- Experience working in Agile / Scrum environments
- Familiarity with data observability frameworks
All your information will be kept confidential according to EEO guidelines.
Salary : $70