1,827 Metadata Management jobs in India

We are looking for a skilled Metadata Management Consultant to join our team. This role involves defining and implementing metadata management strategies and frameworks to ensure effective data governance and data quality across the organization. The ideal candidate will have experience in metadata management tools and practices, along with a solid understanding of data governance principles.

• Exp- 6 to 8 years
• Location- Bangalore

Requirements

Key Responsibilities:

1. Define and implement metadata management frameworks aligned with business objectives.

2. Develop and maintain metadata repositories for various data sources.

3. Collaborate with data stewards and business stakeholders to populate and manage metadata.

4. Ensure compliance with data governance policies and standards related to metadata management.

5. Conduct regular audits and assessments of metadata quality and usage.

6. Provide training and support to teams on metadata management best practices.

7. Analyze and resolve metadata issues to improve data quality and accessibility.

8. Stay updated with industry trends and tools related to metadata management.

Technical Skills:

- Familiarity with metadata management tools (e.g., Alation, Collibra, Informatica).

- Understanding of data governance frameworks and best practices.

- Knowledge of data architecture, data modeling, and data lineage concepts.

- Proficiency in SQL and data querying.

- Experience with data cataloging and data classification.

Required Qualifications:

1. Bachelor’s degree in Computer Science, Information Systems, or related field.

2. 6-8 years of experience in metadata management or data governance roles.

3. Strong understanding of data management principles and practices.

4. Experience with metadata management tools is a significant advantage.

5. Excellent communication and collaboration skills.

6. Strong analytical and problem-solving abilities.

Benefits

Work with one of the Big 4's in India

Data Quality Analyst - Data Governance

We are Reckitt

Human Resources

About the role

The Data Quality Analyst will support the successful implementation of BAU projects and changes by being accountable for mapping, monitoring and analytics of data against required set of data rules before upload to the HR system. The role will be responsible for supporting on organisational restructures, data uploads, imitation of job codes, analysis of data quality and general support of the Global Data Governance analyst activities as necessary.

Your responsibilities

• Understand the business users’ requirements for specific projects
• Lead preparation of data requirements based on business demand understanding for uploads
• Mapping data where required
• Monthly data quality scorecard preparation
• Organising and transforming information into comprehensible structures
• Using tools and techniques to visualise data in easy-to-understand formats, such as diagrams and graphs
• Preparing reports and presentations to be used with internal business clients
• Monitoring data quality and support in fixing corrupt data
• Perform audits, as required, to ensure quality processes exist and are being adhered to.

The experience we're looking for

• Experience of excel and other reporting tools
• Experience and knowledge of SAP Success Factors
• Excellent communication skills with the ability to manage a range of stakeholders. 
• Have a keen interest in data quality
• Be keen to try new things and develop innovative ideas to improve the data quality of the system
• Ability to work well in a team and manage your projects effectively.
• Excellent English language skills both verbal and written. 
• A keen eye for design and attention to detail.

The skills for success

What we offer

Equality

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 Analysts

Overview

We are seeking a highly skilled Data Quality Analyst with 6 to 10 years of experience and a strong

foundation in both business and technical expertise in Investment Banking Domain. The ideal

candidate will be an analytical thinker, adept at problem-solving, reviewing data quality checks, and

proposing new ones. As a Data Quality Analyst, you will ensure the accuracy, consistency, and

reliability of data within the organization.

Key Responsibilities

 Perform comprehensive data quality checks and propose enhancements to existing

processes

Analyze and solve complex problems related to data quality in the Investment Banking

domain

ollaborate with cross-functional teams to ensure data integrity across various systems

upport Business System Analysis, Project Management, and Quality Assurance initiatives

ork on Trade Life Cycle and Management modules, including Front, Middle, and Back-

office operations

tilize tools such as Charles River Investment Management System (CRD), SQL for data

analysis

ngage in extended testing areas, including End to End Performance Testing

onduct Data Validation and Cleansing to identify and rectify errors and inconsistencies,

ensuring high data quality

ontinuously monitor data quality metrics and trends to pinpoint areas needing

improvement

erform Data Quality Assessments and audits to evaluate data quality

ollaborate closely with data engineers, data scientists, and other stakeholders to uphold

data quality standards

aintain detailed documentation of data quality processes and standards

reate and present reports on data quality metrics and improvements to management

Required Skills

trong expertise in investment banking, capital markets - Front, Middle and Back office

operations

roficient in SQL, ETL and various data analysis tools

ell-versed in Charles River IMS (CRD) and its functionalities

xcellent analytical and problem-solving skills

xperienced in quality assurance life cycles and testing methodologies

ffective communicator, capable of engaging with both technical and non-technical

stakeholders

etail-oriented, skilled in identifying and correcting data discrepancies and errors

trong analytical skills for examining data and recognizing patterns or issues

amiliarity with Agile methodology and Atlassian tools is advantageous

echnically proficient with data management tools and software, such as SQL, Excel, and

data visualization tools

nowledge in snowflake

roblem-solving skills to devise solutions for enhancing data quality

xcellent verbal and written communication abilities for collaborating with team members

and stakeholders

elf-motivated and proactive in identifying and resolving data quality issues

trong organizational skills and attention to detail

bility to work independently and as part of a team

ager to learn and adapt to new technologies and methodologies

The individual is responsible for the following:

1. Review, analyze, and work with relevant stakeholders to resolve data quality issues across source systems in scope.

2. Coordinate with data owners and other teams to identify root-cause of data quality issues and implement solutions.

3. Work closely with Data Owners/Owner delegates on data analysis and development data quality (DQ) rules. Work with IT on enhancing DQ controls.

4. End-to-end analysis of business processes, data flows, and data usage to improve business productivity through re-engineering and data governance.

5. Interact with business stakeholders to identify, prioritize, and address data-related needs and issues.

6. Document business requirements and use cases for data-related projects.

7. Manage change control process and participate in user acceptance testing (UAT) activities.

8. Implement data governance policy as a part of projects involved.

9. Identify and escalate issues in a timely manner.

Key Skills:

1. Ability to interact with business and technology teams to understand processes and data usage.

2. Ability to do data analysis and trace data lineage.

3. Capable of working across organization and as part of a cross-functional virtual team.

4. Ability to work and think independently, but within a team-based approach.

5. Problem solver, self-starter, ability to work through an entire issue lifecycle. Ability to effectively prioritize and multi-task.

6. Experience in working on regulatory projects is a plus.

7. Strong communication skills.

Our Vision:

Help IIT Bombay rank among the top engineering and technology institutes worldwide by fostering strong relationships with its alumni, corporations and philanthropists.

About us:

The Indian Institute of Technology Bombay, set up in 1958 as the second IIT, is recognised worldwide as a leader in the field of science and engineering education and research. The Institute was granted the status of 'Institution of Eminence' by the Ministry of Education (the then Ministry of Human Resources Development) on July 9, 2018. IIT Bombay is reputed for the quality of its faculty, cutting edge research, industry relations and the outstanding calibre of students graduating from its undergraduate and postgraduate programmes. The Institute has 17 academic departments, 35 other academic entities (Centres/ Programmes/ Academic facilities/ Hubs/ Externally funded centres and Labs) and three schools. Over the last six decades, more than 75,000 engineers and scientists have graduated from the Institute. It is served by 751 faculty members and about 150 visiting and part-time faculty considered not only amongst the best within the country but also highly recognised in the world for achievements in the field of education and research. On June 4, 2024, IIT Bombay was ranked 1st in India and 118th in the world in the Quacquarelli Symonds (QS) World University Rankings for 2025. On March 12, 2025, IIT Bombay was ranked 28th in Engineering and Technology in the Quacquarelli Symonds (QS) World University Rankings by Subject for 2025.

IITB DRF assists fundraising endeavours by way of donor solicitations, managing donor programs, maintaining financial accounts and reporting details of all activities implemented with alumni donations.

Job Purpose:

As a Data Engineer, you’ll play a pivotal role in building and optimizing data infrastructure that supports fundraising operations, donor analytics, campaign performance tracking, and strategic decision-making. You’ll work across departments to develop robust, scalable, and secure data pipelines, integrating multiple sources to create a unified view of donor behaviour and campaign effectiveness. You will also work on improving the quality of data, enriching the data from various sources, putting strategies in place.

Key Responsibilities:

Design & Build Data Pipelines:

Develop and maintain ETL/ELT pipelines to collect, clean, transform, and store data from various sources including donor management systems (e.g., Salesforce, Raiser’s Edge), marketing platforms, payment processors, and CRM tools.

Data Integration:

Connect and normalize data from external sources like email marketing, social media platforms, donation portal, payment gateways and event platforms.

Database & Warehouse Management:

Design and manage databases and data warehouses to support real-time dashboards and historical analytics.

Collaborate Across Teams:

Work closely with Fundraising, Marketing, Finance, and Analytics teams to understand data needs and translate them into robust technical solutions.

Ensure Data Quality & Security:

To liaise with other functions ensuring the data enrichment and completeness, along with data updation and cleaning from time to time to maintain the data quality. Implement monitoring, validation, and governance practices to ensure data accuracy, compliance (e.g., GDPR), and security.

Support BI & Reporting Tools:

Enable self-service analytics and reporting through tools like Tableau, Power BI, or Looker by ensuring well-modeled, accessible data sources.

Desired Experience/ competencies:

• Bachelor’s degree in computer science, Engineering, Information Systems, or related field.
• 2–5 years of experience in data engineering or similar roles.
• Strong SQL and experience with ETL/ELT frameworks.
• Proficiency in Python or another scripting language.
• Experience with relational and cloud-based data platforms (e.g., Salesforce, Raiser’s Edge, Alma base, Snowflakes, etc.).
• Familiarity with data orchestration tools.
• Experience with fundraising CRM platforms (e.g., Salesforce NPSP, Raiser’s Edge).

Preferred:

• Knowledge of data privacy and compliance in the non-profit sector.
• Experience in donor lifecycle modelling, segmentation, or campaign attribution.