SDET Engineer

Company Description

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com

QA Automation Engineer

Responsibilities

• Design, develop, and maintain

  automation frameworks

  using

  Python

  for data validation and workflow testing.
• Perform

  ETL testing

  to validate data extraction, transformation, and loading processes across multiple data sources.
• Conduct

  Database and Big Data testing

  using SQL and other relevant tools to ensure data integrity and performance.
• Validate end-to-end

  data pipelines

  across

  Azure Data Fabric, Azure Synapse, and Azure Data Factory

  .
• Collaborate with Data Engineering and Development teams to identify quality gaps, define test strategies, and improve automation coverage.
• Develop and execute

  test cases, test scripts, and regression suites

  for large-scale data applications.
• Perform

  data reconciliation and validation

  in distributed environments (Hadoop, Spark, or Databricks).
• Participate in CI/CD automation and support quality gates in

  Azure DevOps

  pipelines.
• Document test results, defects, and ensure traceability from requirements to validation.

Qualifications

• 3+ years

  of experience in

  QA Automation

  with a strong background in

  data testing

  .
• Hands-on experience in

  Python-based automation frameworks

  (PyTest, Unittest, or custom-built).
• Strong SQL skills for

  data validation, profiling, and complex query testing

  .
• Proven experience in

  ETL testing

  and validation of data flows across staging, transformation, and target layers.
• Experience in

  Big Data testing

  (Spark, Hive, HDFS, Databricks, or similar technologies).
• Knowledge of

  Azure Data Fabric, Azure Data Factory, Synapse, and Data Lake

  .
• Good understanding of

  data warehousing concepts, data modeling

  , and

  schema validation

  .
• Experience working with

  CI/CD pipelines

  ,

  Git

  , and

  Azure DevOps

  .