7 Data Cataloguing Jobs

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, our most valuable asset is our people. Here you'll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers, and consumers, worldwide. ZSers drive impact by bringing a client-first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning; bold ideas; courage and passion to drive life-changing impact to ZS. At ZS, we honor the visible and invisible elements of our identities, personal experiences, and belief systemsthe ones that comprise us as individuals, shape who we are, and make us unique. We believe your personal interests, identities, and desire to learn are part of your success here. Learn more about our diversity, equity, and inclusion efforts and the networks ZS supports to assist our ZSers in cultivating community spaces, obtaining the resources they need to thrive, and sharing the messages they are passionate about. **Business Technology:** ZS's Technology group focuses on scalable strategies, assets, and accelerators that deliver to our clients enterprise-wide transformation via cutting-edge technology. We leverage digital and technology solutions to optimize business processes, enhance decision-making, and drive innovation. Our services include, but are not limited to, Digital and Technology advisory, Product and Platform development, and Data, Analytics, and AI implementation. **What you'll do:** - Strong understanding of data management, data cataloging, and data governance best practices. - Enterprise data integration and management experience working with data management, EDW technologies, and data governance solutions. - Thorough understanding of designing and developing data catalog & data assets on industry-leading tools. - Experience with Collibra, Data Quality, and configuring data governance resources. - Management of Enterprise Glossary and development of Collibra/Alation data catalog resources. - Implementing Critical Data Elements, data governance standards, and data quality rules. **What you'll bring:** - Bachelor's or Master's degree in Business Analytics, Computer Science, MIS, or related field. - 1+ years of relevant professional experience in delivering small/medium-scale technology solutions. - Ability to lead project teams, drive end-to-end activities, and strong analytical and problem-solving skills. - Proficiency in programming languages like Python, RDBMS concepts, SQL, data warehousing, and reporting. - Experience with big data concepts, data management, data analytics, and cloud platforms. **Additional Skills:** - Strong verbal and written communication skills. - Familiarity with Big Data Concepts and Cloud Platforms like AWS, Azure, and Google Cloud Platform. - Understanding of productivity tools such as co-pilot and SQL generation. **Perks & Benefits:** ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth, and professional development. Our robust skills development programs, multiple career progression options, internal mobility paths, and collaborative culture empower you to thrive as an individual and global team member. **Travel:** Travel is a requirement at ZS for client-facing ZSers. While some projects may be local, all client-facing ZSers should be prepared to travel as needed to strengthen client relationships and gain diverse experiences. ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law. To Complete Your Application: Candidates must possess or be able to obtain work authorization for their intended country of employment. An online application, including a full set of transcripts, is required to be considered. NO AGENCY CALLS, PLEASE.,

As a Senior Data Governance Executive at our Chief Data Office, you will play a key role in developing, implementing, and maintaining our data governance framework, policies, and procedures. Working closely with the Data Governance Lead, you will collaborate with data owners, stewards, technology teams, and business stakeholders to establish and enforce data standards, policies, and best practices aligned with industry standards and regulatory requirements. Your responsibilities will include developing and implementing a comprehensive data governance framework encompassing data standards, quality rules, metadata management, and stewardship practices. You will bridge the gap between the enterprise Data Office and business data governance stakeholders, partnering with business functions to drive data maturity assessments and remediation plans. Ensuring data quality and integrity is crucial, and you will be responsible for implementing data quality metrics and monitoring processes to maintain data accuracy, completeness, and consistency. Collaborating with data owners and stewards, you will identify and address data quality issues and ensure compliance with regulatory requirements and data security controls. In terms of data stewardship, you will appoint data stewards to oversee specific data assets, provide training and support to ensure effective data asset management, and guide the adoption and optimization of data governance tools like OpenMetadata. You will also implement processes for capturing metadata, data lineage, and usage across key data assets. Tracking KPIs for data governance performance, reporting to executive leadership, and collaborating with business leaders, data owners, and IT teams are essential aspects of this role. Effective communication of data governance policies, procedures, and issues to stakeholders through various channels will be part of your responsibilities. To be successful in this role, you should hold a Bachelor's degree in computer science, Information Technology, Business Administration, or a related field, along with a minimum of 5 years of experience in data governance or data management, preferably in the financial services industry. Strong understanding of data governance principles, frameworks, and best practices, as well as hands-on knowledge of data cataloguing tools, data lineage, and data quality are required. Your collaboration and communication skills will be put to the test as you work on aligning technical governance with business objectives, managing stakeholders, and articulating data governance value to non-technical audiences. Being self-driven, process-oriented, and possessing strong analytical and problem-solving skills are essential traits for this role. While certification in data governance or data management is a nice-to-have, your ability to lead governance initiatives independently, collaborate across business and technical teams, and influence without authority will be key to success in this position.,

As an Assistant Vice President Metadata Support Analyst at HSBC, you will play a crucial role in supporting the implementation of Metadata Management solutions and Business Data Layer. You will work collaboratively with Business, Data, and IT teams to create and maintain source-aligned data products according to agreed templates, guidelines, and principles. Your responsibilities will include engaging with the Data Architecture and Governance team to discover necessary metadata, automate metadata collection, design metadata usage with stakeholders, and ensure the quality and integrity of metadata. Your role will also involve monitoring the overall health and usage of metadata and data products to enhance user experience. You will define key performance indicators (KPIs) to measure the effectiveness of data products, provide ongoing support for metadata implementation, testing, and integration, and offer expertise to enable customers to meet their data requirements independently. Collaboration with cross-functional teams to ensure strategic solutions align with Data Strategy will be essential. To excel in this role, you should have strong analytical and data manipulation skills, particularly in SQL, to provide data solutions, reports, and support for data customers. Previous experience in a Global Data Organisation and familiarity with Data Management activities are required. An understanding of Data and Metadata management, including data cataloguing, as well as experience with Metadata management tools and Data Catalogue tools, is necessary. Knowledge of Data Modelling/Metadata Modelling (MetaModel) and basic understanding of Data products are expected. Ideal candidates will hold a Bachelor's degree or equivalent qualification and possess the ability to work effectively in global and local teams across different time zones. Being a good team player, maintaining strong relationships, and working under pressure with evolving priorities are key attributes for this role. You should be able to clearly communicate concepts and issues, translate theory into practical business solutions, and have experience interacting with senior stakeholders in a global environment. While Asset Management experience is preferred, it is not mandatory. Join HSBC to make a real impact and discover the value you can bring to a global banking and financial services organisation.,

As an Assistant Vice President Metadata Support Analyst at HSBC, you will play a crucial role in supporting the implementation of Metadata Management solutions and Business Data Layer. Your responsibilities will include creating and maintaining source-aligned data products, collaborating with various teams to design and implement metadata usage, ensuring the quality and integrity of Metadata, and defining KPIs to measure the effectiveness of Data Products. Additionally, you will provide ongoing support for metadata/Data products implementation, testing, and integration, as well as expertise to enable customers to be self-sufficient in their data needs. To excel in this role, you should possess strong analytical and data manipulation skills, particularly in SQL, along with previous experience in a Global Data Organisation. A good understanding of Data and Metadata management, experience with Metadata management or Data Catalogue tools, and knowledge of Data Modelling/Metadata Modelling are essential requirements. A typical qualification would include a Bachelor's degree or equivalent. Being a good team player is crucial, as you will collaborate with global and local functional team members in different time zones. Your ability to work effectively under pressure, articulate concepts and issues clearly, and translate theory into practical business solutions will be key to success in this role. Experience in working with senior stakeholders in a global environment is desirable, and Asset Management experience is preferred but not mandatory. If you are looking to make a real impact and be valued for your expertise, join HSBC and be part of a dynamic team that strives to help businesses thrive, economies prosper, and individuals fulfill their hopes and ambitions. Your contributions as an Assistant Vice President Metadata Support Analyst will play a significant role in achieving these goals at HSBC.,

Job Description: Head of AI, Data & Integration Reports to: Global CIO Role Summary We are seeking a grounded yet visionary leader to serve as Head of AI, Data & Integration. This role will oversee enterprise-wide initiatives in data management, analytics, integration, and AI/ML (including Generative AI), enabling the company to make better decisions, operate more efficiently, and unlock new value through data. It is both a strategic and delivery-focused role, with the clear expectation of influencing our transformation journey without disrupting what already works. The ideal candidate brings a builder” mindset, strong business acumen, technical depth in AI and data platforms, and a collaborative approach to driving change. This role will shape our data and AI agenda while directly managing teams and partners involved in Data Governance, Master Data Management, Enterprise Integration, Business Intelligence, and the scalable deployment of AI/ML solutions. Key Responsibilities Enterprise Data & Integration Strategy Lead the enterprise data architecture, integration platforms (Boomi, SAP CPI, etc.), and data engineering roadmap. Establish data standards, pipelines, and models to support operational, financial, and commercial processes. Ensure interoperability across ERP, supply chain, R&D, manufacturing, and commercial systems. AI & Analytics Leadership Define and drive the AI/ML and GenAI strategy — identifying and delivering high-impact use cases across business functions. Build shared, scalable AI capabilities to support knowledge search, process optimization, and intelligent decision support. Collaborate with cross-functional stakeholders to embed data and AI into day-to-day workflows. Data Governance & Quality Lead master data management (MDM), data governance, and data quality initiatives to ensure reliable and compliant data assets. Implement robust frameworks for data stewardship, access control, auditability, and lifecycle management. Align data practices with enterprise compliance standards (e.g., 21 CFR Part 11, GxP, cybersecurity). Organizational Enablement & Innovation Build and mentor a strong internal team covering data engineering, data science, BI/analytics, and integration development. Partner with external vendors, innovation hubs, and platforms to augment capabilities and stay ahead of emerging trends. Create a culture of data literacy, continuous learning, and practical experimentation. Program Execution & Value Delivery Deliver cross-functional AI/data programs with clarity, speed, and business impact. Establish performance metrics to measure ROI, adoption, data quality, and operational efficiency improvements. Ensure successful scaling of AI and data-driven solutions, from proof-of-concept through to enterprise rollout. Required Experience & Qualifications 20+ years in IT or digital transformation roles, with deep experience in enterprise data, integration, and analytics platforms. 7+ years of direct leadership over Big Data/AI/ML initiatives and cross-functional delivery teams. Experience building and scaling data pipelines, governance models, MDM programs, and integration frameworks in complex enterprises. Proven ability to deliver business outcomes using GenAI, ML, and automation. Strong leadership, communication, and stakeholder management skills across business and technical functions. Industry experience in life sciences, pharmaceuticals, or other regulated sectors preferred.

ABOUT THE ROLE Role Description: We are seeking a highly skilled and experienced hands-on Test Automation Engineering Manager with a deep e xpertise in Data Quality (DQ) , Data Integration (DIF) , and Data Governance . In this role, you will design and implement automated frameworks that ensure data accuracy, metadata consistency , and compliance throughout the data pipeline , leveraging technologies like Data bricks , AWS , and cloud-native tools . You will have a major focus on Data Cataloguing and Governance , ensuring that data assets are well-documented, auditable, and secure across the enterprise. In this role, you will be responsible for the end-to-end design and development of a test automation framework, working collaboratively with the team. As the delivery owner for test automation, your primary focus will be on building and automating comprehensive validation frameworks for data cataloging , data classification, and metadata tracking, while ensuring alignment with internal governance standards. will also work closely with data engineers, product teams, and data governance leads to enforce data quality and governance policies . Your efforts will play a key role in driving data integrity, consistency, and trust across the organization. The role is highly technical and hands-on , with a strong focus on automation, metadata validation , and ensuring data governance practices are seamlessly integrated into development pipelines. Roles & Responsibilities: Data Quality & Integration Frameworks Design and implement Data Quality (DQ) frameworks that validate schema compliance, transformations, completeness, null checks, duplicates, threshold rules, and referential integrity. Build Data Integration Frameworks (DIF) that validate end-to-end data pipelines across ingestion, processing, storage, and consumption layers. Automate data validations in Databricks/Spark pipelines, integrated with AWS services like S3, Glue, Athena, and Lake Formation. Develop modular, reusable validation components using PySpark, SQL, Python, and orchestration via CI/CD pipelines. Data Cataloging & Governance Integrate automated validations with AWS Glue Data Catalog to ensure metadata consistency, schema versioning, and lineage tracking. Implement checks to verify that data assets are properly cataloged, discoverable, and compliant with internal governance standards. Validate and enforce data classification, tagging, and access controls, ensuring alignment with data governance frameworks (e.g., PII/PHI tagging, role-based access policies). Collaborate with governance teams to automate policy enforcement and compliance checks for audit and regulatory needs. Visualization & UI Testing Automate validation of data visualizations in tools like Tableau, Power BI, Looker , or custom React dashboards. Ensure charts, KPIs, filters, and dynamic views correctly reflect backend data using UI automation (Selenium with Python) and backend validation logic. Conduct API testing (via Postman or Python test suites) to ensure accurate data delivery to visualization layers. Technical Skills and Tools Hands-on experience with data automation tools like Databricks and AWS is essential, as the manager will be instrumental in building and managing data pipelines. Leverage automated testing frameworks and containerization tools to streamline processes and improve efficiency. Experience in UI and API functional validation using tools such as Selenium with Python and Postman, ensuring comprehensive testing coverage. Technical Leadership, Strategy & Team Collaboration Define and drive the overall QA and testing strategy for UI and search-related components with a focus on scalability, reliability, and performance, while establishing alerting and reporting mechanisms for test failures, data anomalies, and governance violations. Contribute to system architecture and design discussions , bringing a strong quality and testability lens early into the development lifecycle. Lead test automation initiatives by implementing best practices and scalable frameworks, embedding test suites into CI/CD pipelines to enable automated, continuous validation of data workflows, catalog changes, and visualization updates Mentor and guide QA engineers , fostering a collaborative, growth-oriented culture focused on continuous learning and technical excellence. Collaborate cross-functionally with product managers, developers, and DevOps to align quality efforts with business goals and release timelines. Conduct code reviews, test plan reviews, and pair-testing sessions to ensure team-level consistency and high-quality standards. Good-to-Have Skills: Experience with data governance tools such as Apache Atlas , Collibra , or Alation Understanding of DataOps methodologies and practices Familiarity with monitoring/observability tools such as Datadog , Prometheus , or CloudWatch Experience building or maintaining test data generators Contributions to internal quality dashboards or data observability systems Awareness of metadata-driven testing approaches and lineage-based validations Experience working with agile Testing methodologies such as Scaled Agile. Familiarity with automated testing frameworks like Selenium, JUnit, TestNG, or PyTest. Must-Have Skills: Strong hands-on experience with Data Quality (DQ) framework design and automation Expertise in PySpark, Python, and SQL for data validations Solid understanding of ETL/ELT pipeline testing in Databricks or Apache Spark environments Experience validating structured and semi-structured data formats (e.g., Parquet, JSON, Avro) Deep familiarity with AWS data services: S3, Glue, Athena, Lake Formation, Data Catalog Integration of test automation with AWS Glue Data Catalog or similar catalog tools UI automation using Selenium with Python for dashboard and web interface validation API testing using Postman, Python, or custom API test scripts Hands-on testing of BI tools such as Tableau, Power BI, Looker, or custom visualization layers CI/CD test integration with tools like Jenkins, GitHub Actions, or GitLab CI Familiarity with containerized environments (e.g., Docker, AWS ECS/EKS) Knowledge of data classification, access control validation, and PII/PHI tagging Understanding of data governance standards (e.g., GDPR, HIPAA, CCPA) Understanding Data Structures: Knowledge of various data structures and their applications. Ability to analyze data and identify inconsistencies. Proven hands-on experience in test automation and data automation using Databricks and AWS. Strong knowledge of Data Integrity Frameworks (DIF) and Data Quality (DQ) principles. Familiarity with automated testing frameworks like Selenium, JUnit, TestNG, or PyTest. Strong understanding of data transformation techniques and logic. Education and Professional Certifications Bachelors degree in computer science and engineering preferred, other Engineering field is considered; Masters degree and 6+ years experience Or Bachelors degree and 8+ years Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals Strong presentation and public speaking skills.

Candidate with 5–8 years of overall experience in software engineering, including 2-4 years of focused expertise in Data Governance practices such as data cataloguing, data lineage, data quality, data purging, data reliability, data accessibility. Required Candidate profile Strong experience with data governance tools (Ab Initio, Informatica, Atlan, Collibra, Snowflake,Databricks) Hands-on knowledge of data cataloguing, data lineage, data quality, and data access control Perks and benefits To be disclosed post interview