Transformation Lead (ETL + QE)

Overview

Hybrid
Depends on Experience
Full Time

Skills

Transformation Lead (ETL + QE)
Data Quality Testing
Data Validation
QE Transformation
Reporting
BI
ETL testing
Data Testing
ETL
KPIs
Metrics
data governance
security
regulatory
data pipelines
SQL
Power BI dashboards
Snowflake
Airflow
data modeling
data accuracy
integrity

Job Details

Role: Transformation Lead (ETL + QE)

Location: Seattle, WA (Hybrid)

Duration: Fulltime

Job Description:

Required Skills -

Lead experience is a must. Must have good understanding of transformation and change management

Expert experience in Data Validation (Data Quality Testing)

Advanced expertise in QE Transformation, Reporting/ BI and ETL testing

10+ Years experience working in ETL/Data Testing. KPIs/Metrics.

Job Description: Data Tester with expertise in ETL, data pipelines, data validation, Snowflake, Power BI, Airflow, and data modeling. The ideal candidate will ensure data accuracy, integrity, and performance across our data systems.

Must: 10+ Years experience working in ETL/Data Testing Projects bringing lever of Quality maturity transformation by bringing value-adds, Shift-left testing, implementing KPIs/Metrics, bringing innovation through automation and managing a large testing team of offshore-onsite by bringing productivity and ensuring client satisfaction by providing reports and coordinating with Project and Product Team to close GAP in Testing activities.

Key Responsibilities:

  • Validate ETL processes and data pipelines to ensure data accuracy and integrity.
  • Perform data quality checks on large datasets before and after transformations.
  • Develop and execute test cases, test scripts, and SQL queries for data validation.
  • Work with Snowflake to verify data ingestion, transformation, and storage.
  • Test Power BI dashboards and reports for data consistency and performance.
  • Validate and test data models to ensure they meet business requirements.
  • Automate data testing using tools and scripting languages.
  • Identify data anomalies, discrepancies, and inconsistencies in datasets.
  • Collaborate with data engineers and analysts to resolve data issues.
  • Ensure Airflow DAGs execute as expected and handle failures efficiently.
  • Validate data mapping, schema changes, and database migrations.
  • Perform regression testing to ensure new changes do not impact existing data.
  • Monitor data lineage and ensure traceability of data transformations.
  • Conduct performance testing on ETL processes to optimize efficiency.
  • Develop and maintain data validation frameworks and best practices.
  • Verify dimensional and relational data models for accuracy and completeness.
  • Ensure compliance with data governance, security, and regulatory requirements.
  • Troubleshoot data pipeline failures and work on root cause analysis.
  • Participate in agile development cycles, including sprint planning and reviews.
  • Continuously improve testing methodologies and automation for data pipelines.

Education Qualification: Bachelor s degree in computer science, Information Technology, or a related field (or equivalent experience).

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