Data Testing

The Testing Analyst 2 is a developing professional role. Applies specialty area knowledge in monitoring, assessing, analyzing and/or evaluating processes and data. Identifies policy gaps and formulates policies. Interprets data and makes recommendations. Researches and interprets factual information. Identifies inconsistencies in data or results, defines business issues and formulates recommendations on policies, procedures or practices. Integrates established disciplinary knowledge within own specialty area with basic understanding of related industry practices. Good understanding of how the team interacts with others in accomplishing the objectives of the area. Develops working knowledge of industry practices and standards. Limited but direct impact on the business through the quality of the tasks/services provided. Impact of the job holder is restricted to own team.

**Build Data Pipelines**: Create programs using **PySpark** (a powerful data processing tool) to extract data from various sources (like databases and data lakes), clean and transform it, and load it into target systems

**Testing and Validation**: Develop automated tests to ensure the data pipelines are working correctly and the data is accurate. This is like quality control, making sure everything meets the bank's standards

Work with **Hive, HDFS, and Oracle** data sources to extract, transform, and load large-scale datasets

Leverage **AWS services** such as **S3, Lambda, and Airflow** for data ingestion, event-driven processing, and orchestration

Create reusable frameworks, libraries, and templates to accelerate automation and testing of ETL jobs

Participate in code reviews, **CI/CD pipelines**, and maintain best practices in Spark and cloud-native development

Ensures tooling can be run in CICD providing real-time on demand test execution shortening the feedback loop to fully support Handsfree execution

Regression, Integration, Sanity testing, Regression automated suites, reports issues - provide solutions and ensures timely completion

Own and drive automation in Data and Analytics Team to achieve **90%** automation in Data, ETL space.

Design and develop integrated portal to consolidate utilities and cater to user needs.

Supports initiatives related to automation on Data & Analytics testing requirements for process and product rollout into production.

Ensures new utilities are documented and transitioned to testers for execution and supports for troubleshooting in case required.

Monitors and reviews code check-ins from peers and helps maintain project repository.

Ability to work independently as well as collaborate within groups on various projects assigned.

Ability to work in a fast-paced, dynamic environment and manage multiple priorities effectively.

Supports and contributes to automated test data generation and sufficiency.

2-4 years of experience on automation testing across UI, Data analytics and BI reports in the Financial Service industry

Hands on experience on Selenium BDD Cucumber using Java, Python

Extensive knowledge on developing and maintaining automation frameworks, AI/ ML related solutions

Experience on automating BI reports e.g., Tableau dashboards and views validation.

Hands on experience in Python for developing utilities for Data Analysis using Pandas, NumPy etc.

Exposure and some experience on AI related solutions, ML which can help automate faster.

Experience with mobile testing using perfecto, API Testing-SoapUI, Postman/Rest Assured will be added advantage.

Detailed knowledge data flows in relational database and Bigdata systems

Strong knowledge of Oracle SQL and HiveQL and understanding of ETL/Data Testing.

Experience using Bitbucket or equivalent code version control tool.

Experience with CI/CD tools like Jenkins.

Detailed knowledge data flows in relational database and Bigdata (Familiarity with Hadoop (a platform for processing massive datasets)).

Strong experience with PySpark for batch and stream processing deploying PySpark workloads to AWS EKS (Kubernetes)

Proficiency in working on Cloudera Hadoop ecosystem (HDFS, Hive, YARN)

Hands-on experience with ETL automation and validation framework.

Solid understanding of AWS services like S3, Lambda, EKS, Airflow, and IAM

Scripting knowledge in Bash, Python, and YAML

Strong problem-solving and debugging skills

Excellent communication and collaboration abilities to lead and mentor a large techno-functional team across different geographical locations

Strong Acumen and presentation skills

Able to work in an Agile environment and deliver results independently

**Education**:

- Bachelor’s/University degree or equivalent experience**Job Family Group**:
Technology
- **Job Family**:
Technology Quality
- **Time Type**:
Full time
- **Most Relevant Skills**

Please see the requirements listed above.
- **Other Relevant Skills**

For complementary skills, please see above and/or contact the recruiter.-
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