Key Responsibilities
1. Data Pipeline Validation (Must Have)
• Validate end-to-end data pipelines, including ingestion, transformation, and output layers.
• Ensure correctness of data movement across systems (source → staging → target).
• Perform validation of batch and streaming pipelines in Databricks environments.
2. Data Quality & Validation Testing (Must Have)
• Design and execute test cases to validate:
• Data completeness
• Data accuracy
• Data consistency across systems
3. SQL-Based Validation (Must Have)
• Write and execute advanced SQL queries for:
• Data validation and reconciliation
• Data profiling and comparison
4. Python-Based Testing (Must Have)
• Develop validation scripts using Python (e.g., Pandas, PySpark).
• Automate data validation checks where feasible.
• Validate transformation logic implemented in PySpark workflows.
5. Databricks Testing & Validation (Good to Have)
• Execute and validate data processing jobs within Databricks.
• Validate notebooks, workflows, and scheduled jobs.
• Perform test execution and result validation in Databricks workspaces.
• Support testing of Spark-based data transformations
6. Data Pipeline & Workflow Testing (Must Have)
• Validate orchestration workflows and dependencies (pipeline triggers, job sequencing).
• Ensure resilience and correctness of pipeline execution.
• Support validation of integration points across data systems.
7. Collaboration & Analysis
• Work closely with data engineers and data scientists to:
• Understand data models and transformations
• Validate analytical outputs
• Participate in requirement analysis and test strategy definition.
• Provide insights on data quality risks and improvements.
Nice to Have (Optional / Advanced)
• Exposure to AI/ML workflows or LLM-based applications (optional)
Experience
• 3+ years in testing and data validation roles
• Experience in data platform / data engineering environment preferred
Responsibilities
Key Responsibilities
1. Data Pipeline Validation (Must Have)
• Validate end-to-end data pipelines, including ingestion, transformation, and output layers.
• Ensure correctness of data movement across systems (source → staging → target).
• Perform validation of batch and streaming pipelines in Databricks environments.
2. Data Quality & Validation Testing (Must Have)
• Design and execute test cases to validate:
• Data completeness
• Data accuracy
• Data consistency across systems
3. SQL-Based Validation (Must Have)
• Write and execute advanced SQL queries for:
• Data validation and reconciliation
• Data profiling and comparison
4. Python-Based Testing (Must Have)
• Develop validation scripts using Python (e.g., Pandas, PySpark).
• Automate data validation checks where feasible.
• Validate transformation logic implemented in PySpark workflows.
5. Databricks Testing & Validation (Good to Have)
• Execute and validate data processing jobs within Databricks.
• Validate notebooks, workflows, and scheduled jobs.
• Perform test execution and result validation in Databricks workspaces.
• Support testing of Spark-based data transformations
6. Data Pipeline & Workflow Testing (Must Have)
• Validate orchestration workflows and dependencies (pipeline triggers, job sequencing).
• Ensure resilience and correctness of pipeline execution.
• Support validation of integration points across data systems.
7. Collaboration & Analysis
• Work closely with data engineers and data scientists to:
• Understand data models and transformations
• Validate analytical outputs
• Participate in requirement analysis and test strategy definition.
• Provide insights on data quality risks and improvements.
Nice to Have (Optional / Advanced)
• Exposure to AI/ML workflows or LLM-based applications (optional)
Experience
• 3+ years in testing and data validation roles
• Experience in data platform / data engineering environment preferred
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
Backend development (server-side logic, database integration, API connectivity)
Write unit tests and debug code to ensure high-quality software delivery
Collaborate with senior developers and follow best practices
Strong knowledge of Python programming
Hands-on experience with Robot Framework and Appium
Familiarity with Java
Familiarity with JavaScript
Familiarity with Kotlin
Basic understanding of Database Management
Basic understanding of API Development
Good communication skills
Good collaboration skills
Eagerness to learn and grow
Experience with PyTest or other Python testing frameworks
Basic understanding of HTML, CSS, and JavaScript
Experience developing a Robot Framework automation framework from scratch
Experience testing and executing test cases on hardware
Hardware knowledge
AI knowledge
Responsibilities
Backend development (server-side logic, database integration, API connectivity)
Write unit tests and debug code to ensure high-quality software delivery
Collaborate with senior developers and follow best practices
Strong knowledge of Python programming
Hands-on experience with Robot Framework and Appium
Familiarity with Java
Familiarity with JavaScript
Familiarity with Kotlin
Basic understanding of Database Management
Basic understanding of API Development
Good communication skills
Good collaboration skills
Eagerness to learn and grow
Experience with PyTest or other Python testing frameworks
Basic understanding of HTML, CSS, and JavaScript
Experience developing a Robot Framework automation framework from scratch
Experience testing and executing test cases on hardware
Hardware knowledge
AI knowledge
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
Role Category :Programming & Design
Role :Python Automation Test Engineer (Robot Framework)
