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Job Description & How to Apply Below
In this role, you'll be joining our Data Platforms Team within Data Managed Services as a Lead Engineer, Quality Engineering (DaaS - Data Catalogue), responsible for automation for Test Framework Design with new technology in Microsoft Fabric, Microsoft Purview,Test Bed setup, test data management, data quality framework development, test services buildup, test reporting and all automation related work in Quality Engineering.
The software products include (a) Building a Data lakes on the company platform using the platform building blocks DaaS and DMS on Azure cloud Fabric to extract data from vendor distribution channels and transform them to standard LSEG data models, more like an ETL to apply transformation rules and mappings and persist the same to the platform product data lake. (b) The data specialist teams to configure metadata and business rules, data corrections, data dictionary, field dictionary and generate reports.
(c) Building UI/UX for customer to consume the data products based on the data catalogue and business glossary, with product segmentation with rights management. (d) A platform that can on-board multiple data products who have unique requirements and dedicated data sources. The platform capabilities like scheduling, triggering, delivery, interactive data products and contents, and management. The internal team within LSEG who builds software products and solutions for different business units within the organisation.
WHAT YOU'LL BE DOING:
Design, develop, and execute automation scripts using Python Test Framework via BDD / Microsoft Playwright
Identify and create test plans, ensuring thorough coverages for all products.
Integrate automated tests into the CI/CD pipeline, ensuring early defect detection.
Collaborate closely with product, engineering and ops teams to ensure quality across the product lifecycle.
Contribute to the maintenance of test documentation, aligning with LSEG standards and policies.
Stay updated with the latest industry trends, tools, and best practices in test automation.
Demonstrates knowledge of technologies within LSEG and how they relate to various parts of the business.
Work on any number of products that may include creating new automated ETL data feeds, working with data analysts to enhance the existing web tools, refactoring data flow processes, performing support of existing system, performing bug fixes, and prototyping new systems on new hardware.
Executes on the delivery of given tasks with some guidance and oversight.
Develops tools and applications by producing clean and efficient code, may also review others' code when required.
Builds trusting relationships with team and colleagues, collaborating closely with team.
Communicates with clarity and precision in a concise format.
Takes initiative to develop knowledge in technology products and tools through on the job learning, certifications and projects.
WHAT YOU'LL BRING:
Computer science, software engineering, or relevant technical background required.
Proven professional experience in test automation.
Expertise in Python, PySpark, Fabric Lakehouse, like Snowflake, Data Bricks
Experience with Dev Ops CI/CD testing frameworks and integrated with Power BI Reporting or Allure Reports
Experience in creating automation test frameworks using BDD (Behavioural Driven Development) GWT using cucumber, Microsoft Playwright, Python Jbehave, Java script
Expert in API Test Management REST, SOAP, Graph
QL and integration with Jenkins or Azure Dev Ops
Expert in management of test environments in Cloud Infrastructure Azure
Expert in Test Data management and proficient with data sets like ESG, Fundamentals, etc.,
Expert in writing SQL scripts with Big Query, matching with multiple tables, validate the data quality checks with Data Dimensions such as Data Completeness, Data Lineage, Data Referential checks, Data Transformation, Unique Constraints, Data Profiling
Financial Market Industry product development and understand the product life cycle development
Experience in Functional Automation testing in Development environment.
Domain knowledge and understanding of data products and data lakes is nice to have.
Deep understanding of…
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