Need Quality EngineerPFMEA,Control Plan,PPAP,MSA for Gurugram location

Position: Test Engineer

Company : Mayura Consultancy Services

Experience: 2 to 4 yrs

Location : Bangalore

Work Location: Work From Home(WFH)

Apply : Please apply using the URL below Once you complete the application form, we will review your profile and get back to you.

Website :

https://www.mayuraconsultancy.com/careers/test-engineer-opening-mcs?r=jlp

MCS is seeking a meticulous and detail-oriented experienced Test Engineer with minimum of 2 Years of relevant experience to join our team. As a Test Engineer, you will play a crucial role in ensuring the highest standards of quality and efficiency in our products or services. Your primary responsibility will be to assess and evaluate processes, identify areas for improvement, and develop strategies to enhance quality across all aspects of our organization.

Responsibilities

• Develop and implement quality assurance standards, procedures, and methodologies to ensure consistency and excellence in our products, services, or processes.
• Conduct comprehensive evaluations and audits of products, services, or processes to identify deviations, defects, or areas of improvement.
• Maintain detailed records of quality assessments, findings, and recommendations.
• Create and update quality documentation, including standard operating procedures.
• Investigate the root causes of quality issues and collaborate with relevant teams to implement corrective and preventive actions.
• Provide guidance and training to teams and employees on quality standards, best practices, and continuous improvement methodologies.
• Establish feedback mechanisms and channels for employees and customers to report quality-related concerns or suggestions for improvement.
• Prepare and deliver regular reports on quality performance, highlighting areas of success and areas requiring attention.
• Ensure that our processes and products adhere to relevant industry standards, regulations, and compliance requirements
• Drive a culture of continuous improvement by identifying opportunities to streamline processes and enhance quality.

Qualifications:

• Bachelor's degree or Master's degree in a relevant field (Quality Management, Business, Engineering, etc.)
• Proven experience of 1-2 years as a Test Engineer.
• Strong analytical and problem-solving skills.
• Proficiency in quality management tools and methodologies (e.g., Six Sigma, Lean, ISO standards).
• Excellent communication skills.
• Attention to detail and a commitment to precision.
• Ability to work collaboratively with cross-functional teams.
• Familiarity with quality management software and tools.

If you have a keen eye for detail, a passion for process improvement, and the ability to drive positive change, we invite you to apply. This role offers the opportunity to make a significant impact on our organization's quality standards and contribute to our ongoing success. Apply today to be a part of our quality-driven team!

Quality Inspector

Location: Noida / Daman

Department: Quality Assurance

Employment Type: Full Time

Experience: 1–3 Years

Shift: 9–12 Hours

Job Summary

We are looking for a Quality Inspector to conduct routine inspections of incoming raw materials, in-process production, and finished products to ensure compliance with quality standards and specifications.

Key Responsibilities

Inspect incoming raw materials as per specifications.

Conduct in-process quality checks during production shifts.

Inspect finished products before dispatch clearance.

Record inspection results and identify non-conformities.

Segregate and tag rejected or defective materials.

Support root-cause analysis for recurring quality issues.

Maintain inspection registers, quality records, and sample records.

Coordinate with Production and other teams to address quality issues.

Qualification & Experience

ITI / Diploma in Plastic Technology, Quality, or a related field.

1–3 years of experience in quality inspection, preferably in a plastic manufacturing environment.

Knowledge of Injection Moulding / Blow Moulding processes will be an advantage.

Job Title: Corporate Quality MIS Analyst – Automotive / Wiring Harness

Company: Vi-Son Cables Pvt. Ltd.

Location: Mumbai – Corporate Office

Experience: 3–7 Years

Industry: Automotive / Auto Components / Wiring Harness

Job Summary

We are looking for a Quality MIS Analyst with experience in the Automotive, Wiring Harness or Auto Components industry to manage Corporate Quality MIS and reporting. The role will be responsible for consolidating quality data from all plants, analysing KPIs and preparing reports and dashboards for Management.

Key Responsibilities

• Consolidate plant-wise Quality MIS, KPIs and performance reports.
• Analyze PPM, rejection, rework, FPY, customer complaints, CAPA and 8D.
• Prepare MIS reports, dashboards, trend analysis and Management presentations.
• Coordinate with Plant Quality Teams for timely and accurate data.
• Identify quality trends, deviations and improvement areas.
• Maintain standardized Corporate Quality MIS and databases.

Key Requirements

• 3–7 years of experience in Automotive / Wiring Harness / Auto Components Quality.
• Strong knowledge of Quality MIS, Quality KPI reporting and data analysis.
• Proficiency in MS Excel, Pivot Tables, VLOOKUP/XLOOKUP, dashboards and PowerPoint.
• Knowledge of 7 QC Tools, 8D, CAPA and Root Cause Analysis.
• Strong analytical, coordination and communication skills.

Job Description:

As a QA Associate at Binocs, you will play a pivotal role in ensuring the highest quality standards for our software products. With a direct reporting line to the QA Lead, you will be involved in designing, implementing, and executing test plans to identify software issues. This role is ideal for someone with a strong technical background in engineering, experience in fintech or finance software companies, and a passion for quality assurance and detail-oriented testing.

Key Responsibilities:

• Test Plan Development: Create comprehensive and well-structured test plans and test cases based on product specifications.
• Quality Assurance: Execute test cases (manual or automated) and analyze results to ensure software quality.
• Issue Documentation: Document and track bugs, as well as collaborate with the development team to ensure timely resolution.
• Process Improvement: Identify, recommend, and implement improvements in testing processes to enhance efficiency and quality.
• Software Validation: Validate that product features meet requirement specifications and are free of defects.
• Cross-functional Collaboration: Work closely with the product management and development teams to understand product vision and deliver software that aligns with customer and market needs.

Qualifications:

• Bachelor’s degree in Engineering, Computer Science, or related field.
• 2+ years of experience in quality assurance, preferably within fintech or finance software companies.
• Familiarity with software QA methodologies, tools, and processes.
• Experience in writing clear, concise, and comprehensive test plans and test cases.
• Hands-on experience with both white box and black box testing.
• Strong knowledge of software QA metrics, including bug tracking and reporting tools.
• Excellent analytical skills and attention to detail.
• Effective communication skills and the ability to work in a fast-paced environment.

Benefits:

Joining Binocs means being part of a passionate team dedicated to transforming the loan management landscape. We offer a dynamic, innovative environment where your work directly contributes to our vision of efficient, transparent, and data-driven loan management. Our competitive compensation package, including equity, reflects our commitment to attracting and retaining top talent.

About Us:

Binocs.co empowers institutional lenders with next-generation loan management software, streamlining the entire loan lifecycle and facilitating seamless interaction among stakeholders.

Team: Binocs.co is led by a passionate team with extensive experience in financial technology, lending, AI, and software development.

Investors: Our journey is backed by renowned investors who share our vision for transforming the loan management landscape: Beenext, Arkam Ventures, Accel, Saison Capital, Blume Ventures, Premji Invest, and Better Capital.

Quality Assurance Engineer

Location: Remote

Experience: 9–12 Years

Notice Period: Immediate Joiner only

JD:

API Testing: Postman/Swagger

Test Management & Defect Tracking: Jira, Test Director, TFS, Quality Center

Database Testing: SQL (Query Writing & Validation)

Domain Knowledge: US Healthcare Systems, HIPAA, HL7

Methodology: Agile (Scrum)

Job Title: Corporate Quality MIS Analyst – Automotive / Wiring Harness

Location: Goregaon East

Experience: 3–7 Years

Industry: Automotive / Auto Components / Wiring Harness

Role Type: Corporate HO-Based

Job Summary

We are looking for a Corporate Quality MIS Analyst with 3–7 years of experience in the Automotive, Wiring Harness, or Auto Components industry. The candidate will be responsible for consolidating quality data from multiple plants, analysing Quality KPIs, preparing MIS reports and dashboards, and providing management-level insights for quality improvement.

Key Responsibilities

Consolidate plant-wise Quality MIS, KPIs, and performance reports.

Analyse PPM, rejection, rework, FPY, customer complaints, CAPA, and 8D data.

Prepare quality MIS reports, dashboards, trend analysis, and management presentations.

Coordinate with Plant Quality Teams to ensure timely and accurate data submission.

Identify quality trends, deviations, recurring issues, and improvement opportunities.

Maintain standardized Corporate Quality MIS formats, databases, and reporting systems.

Support management reviews with accurate quality data and analytical insights.

Track plant-wise quality performance and highlight gaps against defined targets.

Key Requirements

3–7 years of experience in Quality MIS / Quality Reporting within Automotive, Wiring Harness, or Auto Components.

Strong understanding of Quality KPIs, MIS reporting, and data analysis.

Advanced proficiency in MS Excel, including Pivot Tables, VLOOKUP/XLOOKUP, and dashboards.

Good knowledge of PowerPoint and management presentation preparation.

Knowledge of 7 QC Tools, 8D, CAPA, Root Cause Analysis, PPM, Rejection, Rework, and FPY.

Strong analytical, coordination, communication, and reporting skills.

Experience coordinating with multiple plant/quality teams will be preferred.

About the team

SecurITe’s mission is to build an Agentic‑AI driven security platform that protects critical infrastructure from modern cyber threats. Our focus is on delivering highly performant, resilient, and intelligent network security systems that help defenders stay ahead of adversaries.

About the Role

We’re looking for a seasoned Senior Quality Engineer to provide technical leadership and architectural oversight for our next‑generation cybersecurity AI platform. In this high-impact role, you will define the technical strategy for quality assurance, ensuring our agentic AI transforms cyber defense with unparalleled reliability.

You will be responsible for the end-to-end quality lifecycle, from architectural reviews to the deployment of scalable automation frameworks. Beyond technical execution, you will serve as a mentor to junior team members, fostering a culture of technical excellence and driving the strategy that ensures our solutions meet the rigorous demands of critical infrastructure protection.

What You’ll Do

●    Defining and driving comprehensive QA strategies and roadmaps for the cybersecurity platform.

●    Designing, developing, and executing test plans, test cases, and automated scripts to ensure software quality.

●    Performing functional, regression, performance, scalability and security testing to identify bugs or defects.

●    Collaborating with developers, product managers, and other stakeholders to understand product requirements and testing needs.

●    Identifying, documenting, and tracking software defects, ensuring clear communication of issues and their resolutions.

●    Leading deep-dive root-cause analysis for critical system defects and security vulnerabilities.

●    Conducting thorough reviews of product specifications and software design to identify potential areas of concern before testing.

●    Architecting and designing complex, scalable test automation frameworks to optimize CI/CD velocity.

●    Ensuring the software meets customer and business requirements by validating the functionality and performance.

●    Assisting in continuously improving QA processes, tools, and best practices to enhance software testing efficiency and effectiveness.

●    Supporting user acceptance testing (UAT) and assisting clients with product validation.

●    Mentoring junior and mid-level engineers, providing technical guidance and conducting architectural reviews.

Required Experience

●    A Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field.

●    8-10 years of proven experience in quality engineering, specifically within network cybersecurity, Identity Providers, or AI-integrated platforms.

●    Expertise in manual and automated testing.

●    Deep domain expertise in complex system validation and advanced automation practices at scale.

●    Proficiency in programming languages like Python to build and run automated test scripts.

●    "Strong knowledge of software testing methodologies, performance testing tools (e.g., JMeter, k6), and security traffic generation/simulation tools (e.g., Ixia BreakingPoint, Scapy, or Snort/Suricata traffic generators)."

●    Understanding of continuous integration/continuous deployment (CI/CD) pipelines and version control systems like Git.

●    Strong communication skills for documenting test results and interacting with cross-functional teams.

●    Excellent analytical skills, attention to detail, and problem-solving ability.

●    Ability to work independently as well as collaboratively in a team environment.

●    A curious mindset with a willingness to quickly learn new technologies and testing tools.

Required Skills & Qualifications

●    Familiarity with cloud-based testing environments (GCP, AWS, Azure).

●    Experience with cybersecurity products or cloud services or IDP or Web UI

The Mindset

●    Problem Solver: You thrive on complex, ambiguous challenges and engineer elegant solutions.

●    Ownership‑Driven: You take initiative, move fast, and deliver outcomes without hand‑holding.

●    Continuous Learner: You stay ahead of the curve in AI, ML, and emerging technologies.

●    Startup DNA: You excel in fast‑moving environments where priorities evolve and impact is immediate.

Total exp: 5-8 Years

Client: MRI Software

Location: Vadodara

Budget: Look for decent with experience

Mode interview: 1 Virtual

Mode of Work: Hybrid

QA Engineer:

Job Summary/Objective 

Quality Assurance Engineers at MRI collaborate closely with Product Management and Product Development teams to deliver high-quality, high-performance products for our clients. In this role, QA Engineers are responsible for creating and contributing to the documentation of user stories and acceptance criteria, working alongside product owners and development teams. They define manual and automation testing strategies, tools, scenarios, and plans for both web and mobile products, ensuring comprehensive functional and performance testing. 

 QA Engineers will execute static, dynamic, and performance testing while providing detailed reporting and feedback throughout the development lifecycle. They are expected to demonstrate strong technical skills, including expertise in back-end development, database queries, and keen attention to detail. Effective written, verbal, and organizational communication is essential. 

 In addition, QA Engineers will leverage AI to optimize and automate repetitive tasks, thereby enhancing the overall efficiency and effectiveness of QA processes, ensuring a faster, more accurate testing cycle.

Tools and technology:

1.     Tools: Jira, Xray, TFVC, Git

2.     API: REST, SOAP, SoapUI, Postman

3.     Automation: C#, JavaScript, TypeScript, Ruby, Playwright, SpecFlow

4.     Database: SQL

Key Responsibilities

·      Assuring the high quality of the products

·      Analyze stakeholder and system requirements

·      Design, create and maintain test artifacts (Testplans, Test-Cases, Coverage Matrix)

·      Raise synergies with lower level test stages along the test pyramid

·      Perform end-to-end-, regression- and acceptance tests

·      Document and report test results and defects

·      Create and demonstrate status reports to stakeholders

·      Work with development team on system integration test planning and execution

·      Collaborate with Product Owner to assure correct and complete requirements

·      Follow defined organizational processes and quality standards

·      Participate in Product Development Life Cycle improvements

Required Skills

·      Willingness to identify weaknesses by intensive manual tests

·      Experience with test management tools (Azure Test Plans or similar)

·      Experience of test case detailing, reviews and defect management

·      Experience in functional testing techniques (end-to-end, acceptance, regression, explorational)

·      Understanding of Agile Development Life Cycle methodologies

·      Test Engineer Certification (CSTE, ISTQB) is a plus

·      Strong analytical and problem-solving skills, reliable and self-organized

·      Excellent communication skills in multicultural environments

·      Ideally experience in understanding of C# code

·      Ideally experience in writing automated tests

Job Description – QA & Data Validation Engineer

Experience: 5–6 Years

Location: Pan India

Employment Type: Full-Time

Work Mode: Pan India / Remote or Hybrid as applicable

About the Role

We are looking for an experienced QA & Data Validation Engineer with 5–6 years of hands-on experience in data quality assurance, solution analysis, data validation, SQL, Python, PySpark, Azure Data Factory, Azure Synapse Analytics, and Power BI validation.

The ideal candidate will be responsible for validating large-scale data pipelines, performing source-to-target reconciliation, analyzing business rules, investigating data defects, and ensuring the accuracy, completeness, and consistency of data across source, staging, intermediate, and target systems.

The role requires strong analytical and problem-solving skills along with the ability to work closely with development, data engineering, business, and other stakeholders in an Agile delivery environment.

You will also contribute to the design, development, and maintenance of automated validation frameworks and utilities using Python, SQL, PySpark, Azure Data Factory, and Azure Synapse.

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Key Responsibilities

1. QA & Solution Analysis

- Analyze business and technical requirements to understand data processing and validation needs.

- Participate in requirement analysis sessions and clarify functional and technical requirements with stakeholders.

- Review solution designs, data flows, mapping documents, interface specifications, and business rules.

- Validate that implemented solutions meet defined business and technical requirements.

- Identify gaps, inconsistencies, ambiguities, and potential data quality issues during requirement and solution analysis.

- Translate business requirements into detailed test scenarios, test cases, and validation conditions.

- Perform end-to-end validation of data processing workflows.

- Ensure data is accurately processed from source systems through intermediate layers to final outputs.

- Validate business rules and transformation logic implemented within data pipelines.

2. Test Planning & Execution

- Prepare comprehensive test strategies, test plans, test scenarios, and test cases for data-intensive applications.

- Execute functional, integration, regression, system, and data validation testing.

- Perform positive and negative testing for different data processing scenarios.

- Validate data pipelines across multiple environments, including staging, testing, and production.

- Identify test data requirements and prepare appropriate datasets for validation.

- Execute SQL queries to validate data processing and transformation results.

- Document test results, observations, defects, and validation evidence.

- Track testing progress and communicate status, risks, issues, and dependencies to stakeholders.

3. Data Validation & Reconciliation

- Perform detailed source-to-target data validation and reconciliation.

- Validate source, intermediate, staging, and output datasets.

- Perform record count validation between source and target systems.

- Verify data completeness, consistency, accuracy, and integrity.

- Validate data transformations against defined business rules.

- Perform field-level and record-level comparisons.

- Validate data types, formats, precision, scale, and null handling.

- Verify schema structure, layout, column names, and column sequence.

- Validate mandatory and optional fields.

- Identify missing, duplicate, truncated, or incorrectly transformed records.

- Analyze invalid records, rejected records, and exception datasets.

- Verify exception and reject-handling mechanisms.

- Compare production and staging data to identify discrepancies.

- Perform reconciliation between files, databases, and reporting layers.

- Validate data across different processing stages and identify the root cause of discrepancies.

4. File & Data Processing Validation

- Validate large-scale datasets across multiple file formats.

- Perform validation of:

 - CSV files

 - Delimited files

 - Fixed-width files

 - Excel files

 - Database tables

 - Structured and semi-structured datasets

- Validate file layouts, headers, delimiters, record formats, and column sequences.

- Verify file-level and record-level counts.

- Analyze source, intermediate, and final output files.

- Validate file-to-database and database-to-file reconciliation.

- Identify incomplete, corrupted, malformed, or invalid records.

- Verify data movement and transformation between different storage locations.

- Validate Azure-to-AWS file transfer processes.

- Ensure transferred files are complete and match the expected source datasets.

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5. Defect Investigation & Root Cause Analysis

- Investigate data discrepancies and application/data pipeline defects.

- Perform detailed root cause analysis for data quality and validation failures.

- Analyze source data, transformation logic, pipeline execution, database records, and output datasets to identify defects.

- Collaborate with developers and data engineers to resolve identified issues.

- Reproduce defects and provide detailed technical evidence.

- Perform defect impact analysis.

- Conduct retesting and regression testing after defect resolution.

- Monitor recurring data quality issues and recommend preventive solutions.

- Maintain detailed defect documentation and validation results.

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6. Python Development & Automation

- Develop Python scripts and utilities for data validation and reconciliation.

- Design, develop, and maintain reusable data validation frameworks.

- Automate repetitive data comparison and validation activities.

- Build automated utilities for:

 - Record count validation

 - Data completeness checks

 - Schema validation

 - Column sequence validation

 - Source-to-target comparison

 - Duplicate detection

 - Exception identification

 - Data quality checks

 - Automated reporting

- Develop Python-based validation and reporting utilities.

- Optimize Python scripts for processing large datasets.

- Maintain and enhance existing automation frameworks.

- Implement reusable validation components to improve testing efficiency and coverage.

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7. SQL Development & Data Analysis

- Write complex SQL queries for data analysis and validation.

- Perform data extraction and comparison using SQL Server / SSMS.

- Validate source and target database records.

- Perform joins, aggregations, subqueries, CTEs, and analytical queries as required.

- Develop SQL queries to identify data mismatches, duplicates, missing records, and transformation issues.

- Validate database tables, schemas, columns, constraints, and relationships.

- Perform record count and reconciliation checks using SQL.

- Analyze SQL Server metrics databases.

- Validate data processing results against expected business rules.

- Troubleshoot data discrepancies using SQL queries.

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8. PySpark & Large-Scale Data Processing

- Develop and execute PySpark notebooks for large-scale dataset processing and validation.

- Analyze large volumes of structured and semi-structured data.

- Perform data transformation and validation using PySpark.

- Compare large source and target datasets efficiently.

- Implement data quality and reconciliation checks using PySpark.

- Analyze exception, reject, and invalid datasets.

- Optimize data validation processes for large datasets.

- Work with Azure Synapse notebooks and data processing environments.

---

9. Azure Data Factory & Pipeline Testing

- Design and execute validation scenarios for Azure Data Factory (ADF) pipelines.

- Validate pipeline execution, data movement, transformations, and dependencies.

- Monitor pipeline runs and investigate failures.

- Validate source-to-target data movement through ADF.

- Develop and maintain test pipelines using Azure Data Factory.

- Verify pipeline parameters, triggers, activities, and execution results.

- Validate file ingestion and processing workflows.

- Perform end-to-end testing of data pipelines.

- Investigate pipeline-related data discrepancies and failures.

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10. Azure Synapse Analytics

- Work with Azure Synapse Analytics for data validation and analysis.

- Develop and execute Synapse notebooks using PySpark.

- Validate datasets processed through Synapse pipelines and notebooks.

- Perform data quality and reconciliation checks within Synapse environments.

- Analyze large-scale datasets and processing results.

- Validate data movement between Azure storage, Synapse, databases, and reporting systems.

---

11. Azure Storage & Cosmos DB

- Validate data stored in Azure Storage Accounts and Containers.

- Verify file ingestion, processing, and output data.

- Perform file-level and content-level validation within Azure storage.

- Validate data processing workflows involving Azure Storage.

- Perform data validation in Azure Cosmos DB.

- Verify records, fields, formats, and data completeness within Cosmos DB.

- Investigate discrepancies between source files, Azure storage, databases, and Cosmos DB.

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12. AWS S3 & Azure-to-AWS Validation

- Validate files stored in AWS S3.

- Perform source-to-target validation for files transferred between Azure and AWS.

- Verify file counts, file names, sizes, formats, and record counts.

- Compare source files with transferred S3 files.

- Validate data integrity after cloud-to-cloud file transfers.

- Investigate missing, incomplete, duplicate, or corrupted files.

- Support end-to-end validation of Azure-to-AWS data movement processes.

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13. Metrics, Reporting & Power BI Validation

- Extract and validate source system metrics.

- Validate metrics stored in SQL Server databases.

- Perform reconciliation between source metrics, database metrics, and reporting outputs.

- Validate Power BI dashboards and reports against underlying source data.

- Verify report calculations, KPIs, measures, filters, and aggregations.

- Perform file-to-database-to-Power BI reconciliation.

- Validate data displayed in Power BI against SQL Server and source datasets.

- Identify discrepancies between backend data and dashboard results.

- Support reporting and analytics teams with data validation and troubleshooting.

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14. Production Support & Job Monitoring

- Monitor scheduled data processing jobs and pipelines.

- Perform production validation and health checks.

- Analyze production failures and data discrepancies.

- Support incident investigation and resolution.

- Compare production and staging environments to identify differences.

- Validate production data after deployments and pipeline executions.

- Monitor ECG jobs and provide support for job execution and data processing issues.

- Perform post-production validation and reconciliation.

- Communicate critical production issues and risks to relevant stakeholders.

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15. Agile Delivery & Stakeholder Collaboration

- Work effectively within an Agile/Scrum delivery environment.

- Participate in sprint planning, daily stand-ups, backlog refinement, sprint reviews, and retrospectives.

- Collaborate with Business Analysts, Developers, Data Engineers, DevOps teams, Product Owners, and other stakeholders.

- Provide timely updates on testing progress and issues.

- Participate in requirement clarification and solution discussions.

- Support release planning and production deployment activities.

- Track work items and defects using Rally.

- Ensure testing activities are aligned with sprint and release timelines.

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Required Technical Skills

Mandatory Skills

- 5–6 years of experience in QA / Data Validation / Data Testing / Data Quality Engineering.

- Strong experience in SQL and data analysis.

- Hands-on experience with Python development and automation.

- Experience with PySpark and large-scale data processing.

- Strong experience with Azure Data Factory (ADF).

- Experience with Azure Synapse Analytics / Synapse Pipelines / Notebooks.

- Strong understanding of source-to-target data validation and reconciliation.

- Experience in data completeness, record count, schema, layout, and column validation.

- Experience in defect investigation and root cause analysis.

- Experience validating large datasets and multiple file formats.

- Experience with SQL Server / SSMS.

- Experience with Power BI dashboard/report validation.

- Strong understanding of data pipelines and ETL/ELT processes.

Cloud & Data Platform Experience

- Azure Data Factory

- Azure Synapse Analytics

- Azure Synapse Pipelines

- Azure Synapse Notebooks

- Azure Storage Accounts

- Azure Storage Containers

- Azure Cosmos DB

- Azure Privileged Identity Management (PIM)

- AWS S3

- Azure-to-AWS file transfer validation

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Preferred Skills

- Experience developing automated data validation frameworks.

- Experience building automated reporting and reconciliation utilities.

- Knowledge of ETL/ELT testing methodologies.

- Experience working with very large datasets.

- Experience in production data validation and support.

- Knowledge of cloud-based data platforms.

- Experience with Power BI data reconciliation.

- Experience working in Agile environments.

- Experience with Rally or similar Agile project management tools.

- Familiarity with Microsoft Copilot and AI-assisted productivity/automation tools.

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Key Responsibilities at a Glance

The successful candidate will be responsible for:

- Requirement analysis and clarification

- Business rule validation

- Test planning and execution

- Data quality and data validation

- Source-to-target reconciliation

- Record count and completeness validation

- Schema and layout validation

- Column sequence validation

- Exception and reject data analysis

- Production vs. staging comparison

- SQL-based data analysis

- Python automation

- PySpark development

- Azure Data Factory pipeline testing

- Azure Synapse validation

- Azure Storage validation

- Cosmos DB validation

- AWS S3 validation

- Azure-to-AWS file transfer validation

- Power BI dashboard validation

- SQL Server metrics validation

- Automated reporting

- Defect investigation and root cause analysis

- Production job monitoring and support

- Agile delivery and stakeholder collaboration

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Candidate Profile

We are looking for a detail-oriented, analytical, and technically strong QA/Data Validation professional who can work independently on complex data validation assignments.

The candidate should be comfortable working with large datasets, writing SQL queries, developing Python automation, analyzing PySpark datasets, validating cloud-based data pipelines, and troubleshooting data discrepancies across multiple systems.

Strong communication and stakeholder management skills are essential, as the role requires regular collaboration with technical and business teams.

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Education

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field is preferred.

Experience

5–6 years of relevant professional experience in QA, Data Testing, Data Validation, ETL Testing, Data Quality, Data Engineering QA, or a similar role.

Location

Pan India

Employment Type

Full-Time

Keywords

QA Engineer, Data QA, Data Validation, Data Testing, ETL Testing, Data Quality, SQL, Python, PySpark, Azure Data Factory, ADF, Azure Synapse, Synapse Analytics, Synapse Pipelines, Azure Storage, Cosmos DB, AWS S3, Power BI, SQL Server, SSMS, Data Reconciliation, Source-to-Target Validation, Data Pipeline Testing, ETL QA, Automation Testing, Data Analytics, Root Cause Analysis, Agile, Rally, Cloud Data Testing, Data Engineering QA.