Custom Software Engineer
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : Data Analytics
Good to have skills : NA
Minimum 3 year(s) of experience is required
Educational Qualification : 15 years full time education
Role Summary
A Data and Analytical Testing professional is responsible for ensuring the quality, accuracy, and integrity of data-driven processes, reports, and analytical solutions. This role involves designing and executing test plans, validating data pipelines, and collaborating with cross-functional teams to identify and resolve data-related issues. The ideal candidate will work closely with data engineers, analysts, and business stakeholders to support data quality initiatives, optimize analytical workflows, and contribute to the development of robust business intelligence solutions.
Key Responsibilities
Design, develop, and execute test cases for data pipelines, ETL (Extract, Transform, Load) processes, and analytical models.
Validate data accuracy, completeness, consistency, and integrity across multiple sources and systems.
Identify, document, and track defects, issues, and anomalies in data and analytical outputs.
Collaborate with data engineering, analytics, and business teams to understand requirements and resolve data-related issues.
Automate testing processes where feasible using scripting languages and testing frameworks.
Monitor and report on data quality metrics and testing outcomes.
Support user acceptance testing (UAT) and provide feedback on analytical deliverables.
Ensure compliance with data governance, privacy, and security standards.
Contribute to continuous improvement of testing methodologies, documentation, and best practices.
Required Skills
Proficiency in SQL for data querying and validation.
Experience with data testing tools (e.g., dbt, Talend, Informatica) and scripting languages (e.g., Python, R).
Familiarity with ETL processes, data warehouses, and cloud data platforms (e.g., AWS, Azure, Google Cloud).
Understanding of data modeling, data structures, and analytical frameworks.
Ability to use BI tools (e.g., Tableau, Power BI, Qlik) for data analysis and validation.
Chennai
雇用機会の均等化に関する声明
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