Job Description

JOB DESCRIPTION

Req ID: 349282 

We are currently seeking a Offshore data testers with strong knowledge of data program testing experience to join our team in Bangalore, Karnātaka (IN-KA), India (IN).

A Data QA Engineer ensures data reliability and accuracy by testing data pipelines, ETL processes, and warehouses, focusing on completeness, consistency, and validity for business use, using tools like SQL and Python to build automated tests and find issues, crucial for trustworthy analytics and decisions. They work across the data lifecycle, defining quality rules, profiling data, and collaborating with data engineers and analysts to maintain high data integrity. 

Core Responsibilities

  • Testing & Validation: Designing and running tests for data ingestion, transformation (ETL/ELT), and storage (data warehouses/lakes).
  •  & : Analyzing data structure, identifying anomalies, and setting up continuous monitoring for quality issues.
  • : Building automated test frameworks using Python, Pytest, and SQL to catch defects early.
  • Rule Definition: Creating and implementing data quality rules and metrics (e.g., completeness, accuracy).
  • Collaboration: Working with data engineers, analysts, and business stakeholders to understand needs and resolve defects. 

    • Key Skills & Tools

  • Technical: 6-10+ years experience with SQL (complex queries), Python (Pandas, PySpark), Data Warehousing (DWH), Cloud Platforms (AWS, Azure, GCP), BI Tools (Tableau, Power BI).
  • Analytical: Strong problem-solving, attention to detail, understanding data modeling, data lifecycle, and governance.
  • Methodologies: 6-10+ years experience with familiarity with data testing processes, data governance, and CI/CD. 

    • Thanks & Regards,

    Priyanka M R (She/her)| Global Resource Management | M.+91

    NTT DATA Information Processing Services Private Limited

    Consulting | Industry Solutions | Cloud & Digital Services

    Upcoming OOO:

    From: Gopinath Ramabhadran <>
    Sent: Thursday, January 8, 2026 8:23 PM
    To: Mo Beckley <>; Priyanka M R <>; Mandy Selmer <>
    Subject: Re: DATA QA JD

    Yes this is for both onsite and offshore.

    I think we should aim to get 6-10 years of experience for these roles.

    Regards

    Gopi

    Get

    From: Mo Beckley <>
    Date: Thursday, January 8, 2026 at 9:12AM
    To: Gopinath Ramabhadran <>, Priyanka M R <>, Mandy Selmer <>
    Subject: Re: DATA QA JD

    Hi Gopi,

    Thank you for sharing! Is this the JD for the US role as well? If so, please note that the minimum number years of experience is required for each skill listed under "Key Skills & Tools" in order for the JD to be OFCCP compliant and be placed with recruiting teams. 
    Thank you,

    Mo Beckley (She/Her/Hers)

    Fulfillment Strategist | D&A Practice

    NTT Data Americas, Inc.

    Upcoming Time Off: December 31st, January 1st

    From: Gopinath Ramabhadran <>
    Sent: Thursday, January 8, 2026 8:56 AM
    To: Mo Beckley <>; Priyanka M R <>; Mandy Selmer <>
    Subject: DATA QA JD

    Hello Mo/Priyanka/Mandy

    As discussed please find below the JD for Data QA Tester role.

    A Data QA Engineer ensures data reliability and accuracy by testing data pipelines, ETL processes, and warehouses, focusing on completeness, consistency, and validity for business use, using tools like SQL and Python to build automated tests and find issues, crucial for trustworthy analytics and decisions. They work across the data lifecycle, defining quality rules, profiling data, and collaborating with data engineers and analysts to maintain high data integrity. 

    Core Responsibilities

  • Testing & Validation: Designing and running tests for data ingestion, transformation (ETL/ELT), and storage (data warehouses/lakes).
  •  & : Analyzing data structure, identifying anomalies, and setting up continuous monitoring for quality issues.
  • : Building automated test frameworks using Python, Pytest, and SQL to catch defects early.
  • Rule Definition: Creating and implementing data quality rules and metrics (e.g., completeness, accuracy).
  • Collaboration: Working with data engineers, analysts, and business stakeholders to understand needs and resolve defects. 

    • Key Skills & Tools

  • Technical: SQL (complex queries), Python (Pandas, PySpark), Data Warehousing (DWH), Cloud Platforms (AWS, Azure, GCP), BI Tools (Tableau, Power BI).
  • Analytical: Strong problem-solving, attention to detail, understanding data modeling, data lifecycle, and governance.
  • Methodologies: Familiarity with data testing processes, data governance, and CI/CD. 

    • About NTT DATA

    NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.

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