Data and Analytics Tester SQL, Python, Pyspark

Do you want to be part of an inclusive team that works to develop innovative therapies for patients? Every day, we are driven to develop and deliver innovative and effective new medicines to patients and physicians. If you want to be part of this exciting work, you belong at Astellas

We’re looking for skilled Testers specializing in SQL, Python, and PySpark to join our FoundationX team. As part of this team, your role will involve maintaining operational, scalable data-driven systems that deliver business value.

**Purpose and Scope**:
As a Tester, you will play a crucial role in ensuring the quality and reliability of our pharmaceutical data systems. Your expertise in testing methodologies, data validation, and automation will be essential in maintaining high standards for our data solutions.
- This position is based in Bengaluru and will require some on-site work.

**Essential Skills & Knowledge**:

- SQL Proficiency Strong skills in SQL for data querying, validation, and analysis.
- Experience with complex joins, subqueries, and performance optimization.
- Knowledge of database management systems (e.g., SQL Server, Oracle, MySQL).

Python and PySpark:

- Proficiency in Python for test automation and data manipulation.
- Familiarity with PySpark for big data testing.

Testing Methodologies:

- Knowledge of testing frameworks (e.g., pytest, unittest).
- Experience with test case design, execution, and defect management.

Data Validation:

- Ability to validate data transformations, aggregations, and business rules.
- Understanding of data lineage and impact analysis.

Business Intelligence Tools:

- Strong expertise in creating interactive reports and dashboards using Power BI.
- Knowledge of DAX and Power Automate (MS Flow).

Data Modelling and Integration:

- Ability to design and implement logical and physical data models.
- Familiarity with data warehousing concepts and ETL processes.

Data Governance and Quality:

- Understanding of data governance principles and metadata management.
- Experience ensuring data quality and consistency.

Testing Techniques:

- Familiarity with SQL, Python, or R for data validation and testing.
- Manual and automated testing (e.g., Selenium, JUnit).
- Test Management Tools: Experience with test management software (e.g., qTest, Zephyr, ALM).

Data Analysis:

- Knowledge of statistical analysis and data visualization tools (e.g., Tableau, Power BI).

Pharmaceutical Domain:

- Understanding of pharmaceutical data (clinical trials, drug development, patient records).

Attention to Detail:

- Meticulous review of requirements and data quality.

Collaboration and Communication:

- Ability to work with end users and technical team members. Self-starter who collaborates effectively.

Experience and Agile Mindset:

- Experience with data warehouses, BI, and DWH systems.Analytical thinking and adherence to DevOps principles.**Preferred Skills and Knowledge**:

- Experience working in the Pharma industry. Understanding of pharmaceutical data (clinical trials, drug development, patient records) is advantageous.
- Certifications in BI tools or testing methodologies. Global Perspective: Demonstrated understanding of global pharmaceutical or healthcare technical delivery, providing exceptional customer service and enabling strategic insights and decision-making.

**Responsibilities**:
Development Ownership:

- Take ownership of testing key development projects related to the Data Warehouse and other MI systems
- Collaborate with senior team members in a multi-skilled project team.
- Contribute to efficient administration of multi-server environments.

Test Strategy and Planning:

- Collaborate with stakeholders, data scientists, analysts, and developers to understand project requirements and data pipelines
- Develop comprehensive end-to-end test strategies and plans for data validation, transformation, and analytics.

Data Validation and Quality Assurance:

- Execute manual and automated tests on data pipelines, ETL processes, and analytical models.
- Verify data accuracy, completeness, and consistency.
- Identify anomalies and data quality issues.
- Ensure compliance with industry standards (e.g., GxP, HIPAA).

Regression Testing:

- Validate changes and enhancements to data pipelines and analytics tools.
- Verify data accuracy, consistency, and completeness in QLIK, Power BI, and Tableau reports.
- Monitor performance metrics and identify deviations.

Test Case Design and Execution:

- Create detailed test cases based on business requirements and technical specifications
- Execute test cases, record results, and report defects.
- Collaborate with development teams to resolve issues promptly.

Documentation:

- Maintain comprehensive documentation of test scenarios, test data, and results
- Document test procedures and best practices.

Data Security and Privacy:

- Ensure data security and compliance with privacy regulations (e.g., GDPR)
- Validate access controls and encryption me