Business Development Manager

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.

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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.

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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.

JOB DESCRIPTION

Customer Support - Patient Calling (US Healthcare) Responsibilities: •

Patient calling representatives address patients' concerns about their accounts • Help with billing issues and negotiate to collect unpaid debt • Their duties include creating payment plans and taking patients' payments • When a patient's account has an overdue balance, the patient account representative calls the patient to discuss recovering the payment • Good phone communication skills help working with patients and clearly explaining policies and details. Desired Candidate Profile: • Experience in AR calling is an added advantage • Excellent verbal and written communication skills • Good knowledge in MS Excel and word • Flexible with Night shift timings • Adaptability and willingness to go the extra mile when needed.

EXPERTISE AND QUALIFICATIONS

Competencies required • Basic Computers • Analytical • Excellent Written and Verbal communication •

Domain Venue: Starmark Software Pvt Ltd. Starmark Camelot, No. 6, 1st Main Road, KIADB Export Promotion Industrial Area, Whitefield, Bengaluru/Bangalore - 560066, Karnataka, India

Job Title: Jr. Purchase Engineer / Jr. Purchase Executive (Female Only)

Location: Gandhinagar

Employment Type: Full-Time

Salary: Starting ₹20,000 CTC per month

Experience: Fresher to 2 Years

Job Overview

We are looking for a female Jr. Purchase Engineer / Jr. Purchase Executive. The ideal candidate will be responsible for coordinating with the Purchase, Production, and Planning departments, ensuring smooth procurement operations, and maintaining accurate documentation and follow-ups with suppliers.

Key Responsibilities

• Coordinate between Purchase, Production, and Planning departments to ensure timely material procurement.
• Prepare and release Purchase Orders (POs) accurately and on time.
• Conduct regular follow-ups and calls with suppliers to track order status and delivery schedules.
• Maintain and update purchase records, documents, and supplier databases.
• Support vendor development and assist in identifying cost-saving opportunities.

Qualifications

• Preferred: Engineering Graduate (Mechanical / Electrical / Industrial, etc.) – Fresher or up to 2 years of experience.
• Alternate Qualification: B.Sc., BCA, or B.Com graduates with good communication skills and proficiency in English are also welcome to apply.

Skills Required

• Good computer proficiency, especially in MS Excel and email communication.
• Knowledge of SAP / ERP systems (optional).
• Strong communication and coordination skills.
• Good command of written and spoken English.
• Detail-oriented, organized, and able to multitask effectively.

Job Title:- Business Development Representative (Founding member)

Job Location:- Remote

About Qrata:

Qrata matches top talent with global career opportunities from the world’s leading digital companies including some of the world’s fastest growing start-ups using qrata’s talent marketplaces. To sign-up please visit Qrata Talent Sign-Up

We are currently scouting for Business Development Representative (Founding member)

Our Client Story:

They are building new-age billing and pricing infrastructure for SaaS companies. As SaaS pricing evolves from vanilla subscription based models to more granular usage based models, billing and pricing infrastructure needs to be completely reimagined.

It is founded by two folks who sold their previous start-ups to Snapdeal and Gaana respectively. They have experience at organizations such as Google, Basepair, Elevation Capital, IIT Bombay, IIT Delhi and Harvard Business School. We are funded by marquee global investors, including Bessemer Venture Partners.

What you will do:

We are building our founding team, and are looking for:

• engineers who can optimize for quick iteration, fast deployment and having a great developer experience.
• sales, marketing and growth folks who are excited to push the envelope on GTM (go to market) innovation

You should be excited about learning and meaningfully shaping the trajectory of an early stage startup from Day 0 in its journey.

Qualification:

In order to succeed, SaaS companies need to innovate not only on product, but also GTM (go to market). An innovative, multi-pronged GTM approach is critical to stand out and attract customers.

The good part is that we are building a “pain-killer”, as opposed to a “vitamin”, which makes it much easier to sell and market 🙂 The pain is severe, the product is best in class, and the market is huge - it doesn’t get better than this.

We are selling to the mid-market and enterprise, with a fairly high touch sales process. We are setting up best-in-class sales machinery to scalably and predictably drive revenue.

What you can expect:

• Ownership and autonomy: As a founding team member, you have immense responsibility. You own and drive the execution.
• Learning: You will work on challenging problems and engage in some of the most meaningful work of your life.
• You will have to figure out our Go-To-Market playbook from scratch - channels, messaging, discovery, demos, sales cycle, personas, nurturing, partnerships etc. Expect a whole lot of iteration and first principles thinking.
• Culture:
• We don’t take ourselves too seriously, and know how to have fun :)
• Health of our team is most important to us. Balance work with life - be productive, not busy.
• Being remote first, we thrive via async communication.
• Flexibility: Remote - work from wherever you are in the world; If you prefer coming to office in person, we have a physical space in Indiranagar, Bangalore 🙂
• Compensation: We offer competitive salary with generous ESOPs
• Benefits (for full time roles):
• Health insurance
• Generous vacation policy
• Learning and development budget
• Team events and company offsites
• Maternity and Paternity benefits
• Company laptop

Requirements:

• Bachelor's or Master’s degree in Computer Science, Engineering, or related field.
• Minimum 5+ years of experience in Node.js & Angular development.
• Experience with NoSQL database technologies like MongoDB is must.
• Strong problem-solving skills and the ability to work effectively in a fast-paced environment.
• Excellent communication skills with the ability to articulate technical concepts to non-technical stakeholders.
• Ability to prioritize tasks, manage projects properly and meet project deadlines.
• Experience with version control systems (e.g., Git) and CI/CD pipelines is must.

Responsibilities:

• Lead the Product development team in designing, implementing, and maintaining robust MEAN stack Application.
• Should be able to plan & execute Development Sprints in Jira based on given Feature Documentation.
• Should be able to allocate resources for Sprints and give time estimates.
• Conduct Daily Standup Meetings for Team and make sure of Sprint Progress.
• Provide technical leadership and mentorship to junior developers, guiding them in best practices for MEAN Stack development.
• Collaborate with stakeholders to gather requirements, provide technical insights, and communicate project progress.
• Stay updated with the latest development trends, tools, and technologies, and advocate for their adoption within the team.
• Making sure that we are creating highly scalable and maintainable API’s that meet performance and security requirements.
• Make sure to have at least 90% Test Coverage for NodeJS Backend.
• Conduct detailed code reviews & refactoring and ensure adherence to coding standards, best practices, and project guidelines.
• Optimising frontend components for maximum performance across a vast array of web-capable devices and browsers.
• Develop detailed, annotated wireframes depicting all elements on unique screen types, including content, functional, navigation, and interaction specifications.
• Articulates rationale for approach in the context of both business and user needs.
• Define processes and deliverable that meet project goals and are reasonable within operational, cultural and technology constraints.
• Submit Weekly Sprint & Product Performance Report to Management

• Own the development, testing, and maintenance of native SDKs and Unity on different mobile platforms, their respective OS versions, and devices.
• Partner with [redacted] to design and test new features and products.
• You have the desire to learn new things, try new technology, and seek opportunities to grow and mentor.
• Provide thought leadership in mobile engineering and bring your passion for technology to motivate and inspire on a day to day basis.
• Provide detailed estimates of work and ensure timely delivery of features.
• Produce and ensure delivery of quality, readable, and well-tested code.
• Rely on judgment and experience to plan and accomplish goals in a timely manner.
• Own the elements required to deliver features and results to internal stakeholders.