356 Data Quality jobs in India

Grow. Learn. Thrive. Giant Eagle is where your career can soar high. At Giant Eagle, you are so much more than an employee. You are part of the Family.

About the Company

Since our founding in 1931, Giant Eagle, Inc. has evolved into one of the top 40 largest private corporations in the U.S. and one of the country’s largest food retailers and distributors. With more than 37,000 Team Members and $9.7billion in revenue, we are committed to investing in people, technology, and data to elevate our customer’s experience across multiple touchpoints. It helps us follow on our commitment to serving others and improving our communities.

About Giant Eagle Bangalore

The Giant Eagle GCC in Bangalore is our global capability centre. Our team of more than 350 members at the GCC enables us to expand internal capabilities in the areas such as data analytics, merchandising and eCommerce, quality engineering, and automation to generate insights for faster decision-making and help us accelerate our business strategy. Our team in India plays a pivotal role in helping the company transition to new ways of working by redefining the food and grocery shopping experience for over 4.6 million customers.

Job Description Summary:

The Enterprise Data Management Team for Giant Eagle is critical to accelerating consistent and uniform data services and operational excellence at scale for our enterprise.This role will report into the Director of Enterprise Data Management and will collaborate across the various teams within our business, technology and data & analytic teams. This role delivers the data quality solutions and capabilities as defined by the Director/Manager and provides input into the strategic goals of the Data Quality product team at Giant Eagle – in alignment with the overall Data & Analytics strategy and business objectives.

This role is responsible to deliver best in class data quality capabilities, services and solutions for the enterprise. The Data Quality Engineer will actively engage in the project definition/scoping and requirements phase, effort estimation/adherence, issue escalation, detailed timeline definition and adherence for solutions involving data, technology and business processes. The scope includes the relevant components required to drive the data quality management maturity in support of both operational and analytical excellence at scale – across the dimensions of People, Process, Technology and Data.Data Quality metrics will be delivered in a relevant and meaningful way to the Giant Eagle Leadership Team.

Job Description:

• Experience Required: 3 to 5 years as data quality or data engineer; Experience across a variety of data quality disciplines that include: Data Quality Management, Data Quality Automation or Data designs & architecture; Azure; in particular Azure Data Factory, Azure SQL, Azure Functions, BLOB Storage & Event Grid; GITHUB; DevOps & Agile methodology; Data design for improving business operations & propelling BI / Analytics
• Experience Desired: Databricks & Graph DB; ETL, ELT & Data Integration; Retail data, systems and application experience
• Education Desired: Bachelor's degree
• General SQL Knowledge / .net / C#

Job Responsibilities

• Architect solutions that encompass Data Quality platform & broader data ecosystem
• Design & engineer new data qualities capabilities & automation: Design & development of automated data quality jobs / workflows; Design & development of data quality platform in Azure; Assist with QA, DEV and Prod environment deployments; Assist with creation of testing plans, resolve any defect associated with development
• This role will liaise across all relevant areas and with stakeholders at any level both within IT DnA team and across all function areas to deliver data quality capabilities
• Engage with collaborative and proactive approach to solving key data needs
• Define thorough workflow processes that enhance efficiency, minimize human touch and ensure high data quality results
• Bring best-in-class and right sized Data Quality solutions to life at Giant Eagle
• Design and deliver Data Quality solutions in a highly scalable, collaborative & agile manner
• Depth of retail and/or product business process knowledge across disciplines required for successful Data Quality designs.
• Leverage a data centric approach across all demands to build once and deploy many
• Ensure solutions meet stability concerns for ongoing maintenance and support.
• Adhere to agreed upon Product/Project Management principles to ensure work delivery alignment to strategic imperatives
• Produce all management reports completely, accurately and on time
• Participate in an on-call support rotation

The Data Quality Stable Team is part of the Data Governance & Data Management function. There are responsible to:

Ensure the Volvo Group get the capabilities and support to enable business appointed stakeholders to monitor and improve the quality of their data.

Establish continuous data quality improvement process.

Provide tools, trainings, standards in the area of Data Quality.

What is expected from you?

Drive workshops with the business analyst to understand their business context and to collect their needs around data quality pain points.

Collaborate closely with Business Analysts and with business stakeholders to profile data, build Data Quality measurement, implement Data quality dashboards.

Access, manipulate, query, and analyze data using different software, tools (IDMC, Databricks, SQL, etc) and techniques.

Design, develop, and implement Data Quality pipelines leveraging Data Quality modules (Data Profiling, Data Quality, and Data Integration) in IDMC.

Conduct quality assurance activities to validate the effectiveness of Data Quality pipelines and ensure compliance with established data quality standards.

Perform thorough testing and validation of Data Quality processes, including unit testing, integration testing, performance testing and user acceptance testing.

Document Data Quality processes, including design specifications, testing procedures, and operational guidelines to ensure clarity and maintainability.

Collaborate with domain data stewards and business stakeholders to define data quality requirements and establish metrics for measuring data quality.

Monitor and troubleshoot Data Quality pipelines, identifying and resolving issues to maintain optimal performance and reliability.

Implement best practices for data quality management, including data cleansing, enrichment, and transformation techniques.

Participate in continuous improvement initiatives to enhance data quality processes and tools.

Provide training and support to team members and stakeholders on Data Quality tools and methodologies.

Do you dream big? We do too, and we are excited to grow together. In this role, you will bring:

University degree, with a passion for data.

Hands-on experience with Informatica IDMC, specifically in Data Profiling, Data Quality and Data Integration modules. Minimum 4 years’ experience with Informatica

DQ modules

Strong understanding of Data Quality concepts, including data profiling, cleansing, and validation. Minimum 4/5 years on a DQ project

Experience with ETL solutions

Experience with quality assurance methodologies and testing frameworks.

Basic understanding of MS Azure.

Familiarity with Data Governance & Management principles.

Experience in agile setups, using DevOps or similar.

Strong analytical, problem-solving, and troubleshooting skills.

Good ability to link business needs and developments

Excellent communication and collaboration skills.

Proficiency in English for international projects.

Nice to have: Experience developing with Power BI

Work from office- all 5 days

*Data QA*

*(ETL+ DWH Testing and Cloud Testing - AWS - S3 & Glue & Azure + SQL Server - Writing SQL Queries + Snowflake + ADF + API Testing)*

6 - 10 yrs

Must have technical skills:

Strong understanding of Boomi or any other integration tool like MuleSoft, Informatica, Talend, Workato, etc.

Experience with Data Bricks

Indepth knowledge of ETL Testing

Experience writing SQL Queries

Good Technical Documentation skills.

Strong communication skills, with the ability to interact effectively with technical and non-technical stakeholders.

Good to have skills:

Data Testing on AWS using Athena.

Knowledgeable in running and troubleshooting AWS Glue Jobs.

Understanding of Data Warehousing.

Knowdge on Python and Apache Spark.

11:00 am to 8 pm

(Candidate has to be flexible, may require overlap EST as per project need)

Position- 1

Model- Hyrbrid

Candidate has to work 2/3 days from office in a week

Location- (Bangalore, Pune, Mumbai, Hyderabad, Noida)

Duration- 1 year

Data Quality Analyst (DQ Analyst)

Locations: Bangalore, Pune, Chennai, Hyderabad

Notice Period: Immediate

Mandate Skills

• Data Governance
• Data Management
• Strong focus on Data Quality

Key Responsibilities

• Lead change and project management efforts across Data Quality initiatives
• Collaborate with IWPB markets and stakeholders to align with Data Quality governance objectives
• Analyze the Data Quality portfolio to identify trends and provide actionable insights
• Deliver high-quality MI reporting and visualizations for senior stakeholders
• Prepare program update decks and respond to escalations promptly
• Support the management of Data Quality Issues and Data Quality Measurement frameworks

What We’re Looking For

• 8+ years of experience in Data Governance, Data Management, and especially Data Quality
• Expertise in one or more areas:
• Data Quality Measurement and Reporting
• Data Quality Issues Management
• Data Governance Frameworks
• Excellent stakeholder management and communication skills
• Proven experience in project/change management and reporting/visualization

Roles & Responsibilities :

Data Quality, Modelling & Design Thinking

• Lead, mentor, and inspire a team of data analysts and engineers, fostering a collaborative, innovative, and high-performance culture.
• Oversee the design, implementation, and continuous improvement of data quality models using SAP MDG, Azure, and Power Platform technologies. Guide the team to develop appropriate conceptual data models foundational to physical data model creation.
• Engage closely with technology and business stakeholders to gather requirements, identify improvement areas, and clearly articulate the business value of data quality use cases including cleansing, validation, and enrichment.
• Demonstrate deep understanding of the Data Quality value chain—from Critical Data Elements (CDEs) to Data Quality KPIs—and how it integrates with overarching Data Governance frameworks. Lead and manage within this context effectively.
• Facilitate workshops and training sessions to promote data quality awareness, best practices, and a culture of continuous improvement across the organization.
• Conduct performance evaluations, provide coaching, and identify opportunities for the professional development of team members.
• Proactively identify and escalate data quality risks or hidden issues to the Data Quality Manager for resolution.

Dashboarding & Workflow Management

• Conceptualize, design, and deploy robust data quality dashboards using Power BI to monitor and visualize data health effectively.
• Develop escalation paths and workflows with alerts that notify process and data owners of unresolved data quality issues, ensuring timely remediation.
• Collaborate with IT and analytics teams to incorporate cutting-edge technologies such as AI, Machine Learning, and cognitive science to enhance data quality monitoring and automation.

Data Quality Improvement Plans

• Partner with business functions and projects to develop and embed sustainable data quality improvement plans, fostering business ownership and accountability.
• Define and track measurable targets for data quality maturity, actively monitoring progress and intervening when improvements fall short of expectations.
• Support data clean-up initiatives that improve the accuracy and reliability of existing data landscapes.

Project Delivery & Oversight

• Lead and coordinate Data Quality Analysts in executing data profiling, conversion criteria establishment, and resolution of complex technical and business data quality issues.
• Own the detailed project delivery plan for multiple concurrent data quality programs, ensuring clarity on roles, responsibilities, and timelines using effective RACI frameworks.
• Drive cross-functional alignment and successful delivery of data quality objectives within large-scale enterprise programs.

Qualifications

Educational qualification:

B.E

Experience :

• 11 to 15 years of comprehensive experience in Data Management, preferably within the Oil & Gas or Financial Services/Banking industries.
• Proven expertise in working with complex data models and structures, with strong capability to deeply analyze, design, and optimize these models for enhanced data quality and usability.
• Extensive experience in Data Quality Management, including governance practices, Data Quality Issue (DQI) management—covering root cause analysis, remediation, and solution identification. Familiarity with facilitating governance forums including preparation of papers, ensuring quorum, and publishing meeting minutes.
• In-depth knowledge of Critical Data Element (CDE) identification and Data Lineage, including identifying authoritative data sources. Strong understanding of relevant KPIs and data quality measurement frameworks.
• Experience of having worked with senior stakeholders across multiple data domains, business units, Chief Data Office (CDO), and technology teams. Comfortable operating within global, multi-time zone environments.
• Ability to work effectively in dynamic, fast-changing environments, with strong prioritization skills and the ability to work independently with minimal supervision.

About QualityKiosk Technologies

QualityKiosk Technologies is a leading independent Quality Engineering (QE) and digital transformation provider, helping businesses deliver high-performing, user-friendly applications. Founded in 2000, the company offers services in QA automation, performance assurance, intelligent automation (IA), robotic process automation (RPA), customer experience management, SRE, cloud, data analytics, and more. With a global presence in 25+ countries and a team of 4,000+ professionals, QualityKiosk supports major players across banking, e-commerce, telecom, automotive, insurance, OTT, and pharmaceuticals. Recognized by Forrester, Gartner, and others, it serves 50 of India’s Fortune 100 and 18 of the global Fortune 500 companies. Focused on innovation and rapid execution, the company aims for 5X growth in revenue and workforce over the next five years.

Job Description

Location: Mahape

Experience: 2 years

Early Joiners preferred!

Strategic Responsibilities

• Support the development of the Data Strategy.
• Assist the DQ Lead in implementing data governance frameworks, policies, and standards.
• Help build the Data Governance Office as a center of excellence promoting a data-driven culture.
• Monitor industry and regulatory trends to guide data initiatives.
• Promote data quality and position data as a strategic asset.

Core Responsibilities

• Support reporting on data quality performance and standards.
• Develop and maintain data quality rules and profiling tools using Informatica DQ.
• Contribute to data catalog artifacts (definitions, lineage, standards).
• Maintain organizational reference data.
• Provide expertise on systems and processes to improve data quality.

Additional Accountabilities

• Create data quality dashboards and monitoring tools.
• Support RCA and business teams with data quality analysis.

Communication

• Build strong relationships across business units and support functions.
• Engage with vendors, data partners, consultants, and regulators.

Key KPIs

• Delivery of DQ roadmap
• Reduction in high-priority data issues
• Improved stakeholder satisfaction
• Measurable improvements in data quality

Decision-Making Scope

• Advise on data governance implementation and strategic priorities.
• Recommend budget allocations for data initiatives.

Qualifications & Experience

• Bachelor’s degree, 2+ years in data roles
• Experience in data quality, governance, and financial services.
• Skilled in Informatica DQ, SQL, and dashboard tools.
• Strong analytical, communication, and stakeholder management skills