Factspan
Experience:
8+ Yrs
About the Role We are seeking a highly skilled Lead QA Engineer to join our Adobe ESP POD team. This role requires a strong background in Quality Engineering, Test Automation, and Data Validation within large-scale cloud-based data pipelines. You will lead end-to-end quality efforts for data ingestion, transformation, and integration pipelines on Google Cloud Platform (GCP), ensuring seamless integration with Adobe Experience Platform (AEP). The role is highly collaborative, demanding close interaction with data engineers, business stakeholders, and product teams to guarantee accuracy, performance, and reliability of all data flows and APIs.
Key Responsibilities
Quality Strategy & Leadership
Define and implement the overall QA strategy, frameworks, and best practices for data pipelines, APIs, and cloud-native workloads.
Lead and mentor a team of QA engineers, fostering a culture of automation-first and continuous quality.
Test Planning & Automation
Design robust test plans, test cases, and automated test suites for data ingestion pipelines (BigQuery, GCS, Dataflow, Composer).
Build automated ETL data validation frameworks ensuring source-to-target (S2T) mapping accuracy, data transformations, and aggregations.
Develop API testing strategies leveraging Python, Postman, PyTest, and REST frameworks.
Data Quality & Governance
Validate data completeness, accuracy, and consistency across GCP and Adobe Experience Platform.
Implement automated data reconciliation and anomaly detection scripts using SQL and Python.
Collaborate with Data Governance teams to enforce data quality metrics.
Integration & Performance Testing
Ensure flawless integration of customer profile data between GCP and AEP.
Conduct performance, scalability, and load testing for data pipelines and APIs.
Verify orchestration processes using Cloud Composer meet reliability SLAs.
Partner with business stakeholders to validate S2T mapping requirements.
Document QA strategies, reusable automation frameworks, and validation templates.
Contribute to architecture discussions, highlighting quality considerations early in the design phase.
Must-Have Skills
Strong expertise in GCP (BigQuery, GCS, Dataflow, Cloud Composer).
Advanced SQL for large-scale data validation and profiling.
Python programming for automation frameworks, test scripts, and data validation.Hands-on experience with API testing & automation.
Proven background in QA leadership, with experience building and scaling automation teams.
Good-to-Have Skills
Knowledge of Adobe Experience Platform (AEP) integrations.
Familiarity with Performance Marketing Solutions (e.g., Wunderkind).
Exposure to CI/CD pipelines (GitLab, Jenkins, Cloud Build).
Understanding of data governance, lineage, and cataloging tools.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology
Industries
IT Services and IT Consulting
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8+ Yrs
About the Role We are seeking a highly skilled Lead QA Engineer to join our Adobe ESP POD team. This role requires a strong background in Quality Engineering, Test Automation, and Data Validation within large-scale cloud-based data pipelines. You will lead end-to-end quality efforts for data ingestion, transformation, and integration pipelines on Google Cloud Platform (GCP), ensuring seamless integration with Adobe Experience Platform (AEP). The role is highly collaborative, demanding close interaction with data engineers, business stakeholders, and product teams to guarantee accuracy, performance, and reliability of all data flows and APIs.
Key Responsibilities
Quality Strategy & Leadership
Define and implement the overall QA strategy, frameworks, and best practices for data pipelines, APIs, and cloud-native workloads.
Lead and mentor a team of QA engineers, fostering a culture of automation-first and continuous quality.
Test Planning & Automation
Design robust test plans, test cases, and automated test suites for data ingestion pipelines (BigQuery, GCS, Dataflow, Composer).
Build automated ETL data validation frameworks ensuring source-to-target (S2T) mapping accuracy, data transformations, and aggregations.
Develop API testing strategies leveraging Python, Postman, PyTest, and REST frameworks.
Data Quality & Governance
Validate data completeness, accuracy, and consistency across GCP and Adobe Experience Platform.
Implement automated data reconciliation and anomaly detection scripts using SQL and Python.
Collaborate with Data Governance teams to enforce data quality metrics.
Integration & Performance Testing
Ensure flawless integration of customer profile data between GCP and AEP.
Conduct performance, scalability, and load testing for data pipelines and APIs.
Verify orchestration processes using Cloud Composer meet reliability SLAs.
Partner with business stakeholders to validate S2T mapping requirements.
Document QA strategies, reusable automation frameworks, and validation templates.
Contribute to architecture discussions, highlighting quality considerations early in the design phase.
Must-Have Skills
Strong expertise in GCP (BigQuery, GCS, Dataflow, Cloud Composer).
Advanced SQL for large-scale data validation and profiling.
Python programming for automation frameworks, test scripts, and data validation.Hands-on experience with API testing & automation.
Proven background in QA leadership, with experience building and scaling automation teams.
Good-to-Have Skills
Knowledge of Adobe Experience Platform (AEP) integrations.
Familiarity with Performance Marketing Solutions (e.g., Wunderkind).
Exposure to CI/CD pipelines (GitLab, Jenkins, Cloud Build).
Understanding of data governance, lineage, and cataloging tools.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology
Industries
IT Services and IT Consulting
#J-18808-Ljbffr