119 Metadata Management Jobs - Page 3

Data Modeler- Primary Skills: Data modeling (conceptual, logical, physical), relational/dimensional/data vault modeling, ERwin/IBM Infosphere, SQL (Oracle, SQL Server, PostgreSQL, DB2), banking domain data knowledge (Retail, Corporate, Risk, Compliance), data governance (BCBS 239, AML, GDPR), data warehouse/lake design, Azure cloud. Secondary Skills: MDM, metadata management, real-time modeling (payments/fraud), big data (Hadoop, Spark), streaming platforms (Confluent), M&A data integration, data cataloguing, documentation, regulatory trend awareness. Soft skills: Attention to detail, documentation, time management, and teamwork.

Proficiency in data modeling tools such as ER/Studio, ERwin or similar. Deep understanding of relational database design, normalization/denormalization, and data warehousing principles. Experience with SQL and working knowledge of database platforms like Oracle, SQL Server, PostgreSQL, or Snowflake. Strong knowledge of metadata management, data lineage, and data governance practices. Understanding of data integration, ETL processes, and data quality frameworks. Ability to interpret and translate complex business requirements into scalable data models. Excellent communication and documentation skills to collaborate with cross-functional teams.

Project description We are seeking a highly skilled Data Modelling Expert with deep experience in the Avaloq Core Banking platform to join our technology team. The ideal candidate will be responsible for designing, maintaining, and optimizing complex data models that support our banking products, client data, and regulatory reporting needs. This role requires a blend of domain expertise in banking and wealth management, strong data architecture capabilities, and hands-on experience working with the Avaloq platform. Responsibilities Design, implement, and maintain conceptual, logical, and physical data models within the Avaloq Core Banking system. Collaborate with business analysts, product owners, and Avaloq parameterisation teams to translate business requirements into robust data models. Ensure alignment of data models with Avaloq's object model and industry best practices. Perform data profiling, quality checks, and lineage tracing to support regulatory and compliance requirements (e.g., Basel III, MiFID II, ESG). Support integration of Avaloq data with downstream systems (e.g., CRM, data warehouses, reporting platforms). Provide expert input on data governance, metadata management, and model documentation. Contribute to change requests, upgrades, and data migration projects involving Avaloq. Collaborate with cross-functional teams to drive data consistency, reusability, and scalability. Review and validate existing data models, identify gaps or optimisation opportunities. Ensure data models meet performance, security, and privacy requirements. Skills Must have Proven experience (5+ years) in data modelling or data architecture, preferably within financial services. 3+ years of hands-on experience with Avaloq Core Banking Platform, especially its data structures and object model. Strong understanding of relational databases and data modelling tools (e.g., ER/Studio, ERwin, or similar). Proficient in SQL and data manipulation in Avaloq environments. Knowledge of banking products, client lifecycle data, and regulatory data requirements. Familiarity with data governance, data quality, and master data management concepts. Experience working in Agile or hybrid project delivery environments. Nice to have Exposure to Avaloq Scripting or parameterisation is a strong plus. Experience integrating Avaloq with data lakes, BI/reporting tools, or regulatory platforms. Understanding of data privacy regulations (GDPR, FINMA, etc.). Certification in Avaloq or relevant financial data management domains is advantageous. Other Languages EnglishC1 Advanced Seniority Senior

Data Governance Specialist Req number: R5477 Employment type: Full time Worksite flexibility: Remote Who we are CAI is a global technology services firm with over 8,500 associates worldwide and a yearly revenue of $1 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise. Job Summary We are looking for a motivated Data Governance Specialist ready to take us to the next level! If you are strong in creating and maintaining integrations between data systems and data governance tools and are looking for your next career move, apply now Job Description We are looking for a Data Governance Specialist to develop and maintain Collibra workflows to support data governance initiatives. This position will be Full Time and remote. What You’ll Do Develop and maintain Collibra workflows to support data governance initiatives. Create and maintain integrations between data systems and data governance tools. Write and maintain data quality rules to measure data quality. Work with vendors to troubleshoot and resolve technical issues related to workflows and integrations. Work with other teams to ensure adherence to DG policies and standards. Assist in implementing data governance initiatives around data quality, master data, and metadata management. What You'll Need Required: Experience: 5-7 years Strong programming skills. Knowledge of system integration and use of middleware solutions. Proficiency in SQL and relational databases. Understanding of data governance, including data quality, master data, and metadata management. Willingness to learn new tools and skills. Preferred Proficient with Java or Groovy. Proficient with Mulesoft or other middleware. Proficient with Collibra DIP, Collibra Data Quality, and DQLabs. Experience with AWS Redshift, and Databricks. Physical Demands Ability to safely and successfully perform the essential job functions Sedentary work that involves sitting or remaining stationary most of the time with occasional need to move around the office to attend meetings, etc. Ability to conduct repetitive tasks on a computer, utilizing a mouse, keyboard, and monitor Reasonable accommodation statement If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to application.accommodations@cai.io or (888) 824 – 8111.

Define, implement, & enforce data governance policies & standards to ensure data quality, consistency, & compliance across the organization Collaborate with data stewards, business users, & IT teams to maintain metadata, lineage, & data catalog tools

ABOUT THE ROLE Role Description: You will play a key role in the implementation and adoption of the data governance framework which will modernize Amgen's data ecosystem, positioning Amgen as a leader in biopharma innovation. This role leverages state-of-the-art technologies, including Generative AI, Machine Learning, and integrated data . This role involves working closely with business stakeholder and data analysts to ensure implementation and adoption of the data governance framework. You will collaborate with Data Product Owners, Data Stewards and technology teams to increase the trust and reuse of data across Amgen. Roles & Responsibilities: Responsible for the execution of data governance framework for a given domain of expertise (Research, Development, Supply Chain, etc.). Contribute to the operationalization of the Enterprise data governance framework and aligning broader stakeholder community with their data governance needs, including data quality, data access controls, compliance with privacy and security regulations, foundational master data management, data sharing, communication and change management. Works with Enterprise MDM and Reference Data to enforce standards and data reusability. Contribute to the cross functional alignment in his/her domain(s) of expertise to ensure adherence to Data Governance principles. Maintain documentation on data definitions, data standards, data flows, legacy data structures / hierarchies, common data models, data harmonization etc. for assigned domains. Partner with business teams to identify compliance requirements with data privacy, security, and regulatory policies for the assigned domains Jointly with Technology teams, business functions, and enterprise teams (e.g., MDM, Enterprise Data Fabric, etc.) delivers data foundations. Build strong relationship with key business leads and partners to ensure their needs are met. Functional Skills: Must-Have Functional Skills: Technical skills (Advanced SQL, Python etc) with knowledge of Pharma processes with specialization in a domain (e.g., Research, Clinical Trials, Commercial, etc.) Experience of working with or supporting systems used to data governance framework. E.g. Collibra, Alation General knowledge of data management, common data models, metadata management, data quality, master data management, data stewardship, data protection, etc. Experience with data products development life cycle, including the enablement of data dictionaries, business glossary to increase data products reusability and data literacy. Customer focused with excellent written and verbal communication skills who can confidently work with internal Amgen business stakeholders and external service partners on business process and technology topics Excellent problem-solving skills and a committed attention to detail in finding solutions Good-to-Have Functional Skills: Experience with Agile software development methodologies (Scrum) Soft Skills: Excellent analytical skills Ability to work effectively with global, virtual teams Ability to manage multiple priorities successfully Team-oriented, with a focus on achieving team goals Ability to build business relationships and understand end-to-end data use and needs. Strong verbal and written communication skills Basic Qualifications: Experience with 5 - 9 years of experience in Business, Engineering, IT or related field

ABOUT THE ROLE Role Description: We are seeking a Data Solutions Architect with deep expertise in Biotech/Pharma to design, implement, and optimize scalable and high-performance data solutions that support enterprise analytics, AI-driven insights, and digital transformation initiatives. This role will focus on data strategy, architecture, governance, security, and operational efficiency, ensuring seamless data integration across modern cloud platforms. The ideal candidate will work closely with engineering teams, business stakeholders, and leadership to establish a future-ready data ecosystem, balancing performance, cost-efficiency, security, and usability. This position requires expertise in modern cloud-based data architectures, data engineering best practices, and Scaled Agile methodologies. Roles & Responsibilities: Design and implement scalable, modular, and future-proof data architectures that initiatives in enterprise. Develop enterprise-wide data frameworks that enable governed, secure, and accessible data across various business domains. Define data modeling strategies to support structured and unstructured data, ensuring efficiency, consistency, and usability across analytical platforms. Lead the development of high-performance data pipelines for batch and real-time data processing, integrating APIs, streaming sources, transactional systems, and external data platforms. Optimize query performance, indexing, caching, and storage strategies to enhance scalability, cost efficiency, and analytical capabilities. Establish data interoperability frameworks that enable seamless integration across multiple data sources and platforms. Drive data governance strategies, ensuring security, compliance, access controls, and lineage tracking are embedded into enterprise data solutions. Implement DataOps best practices, including CI/CD for data pipelines, automated monitoring, and proactive issue resolution, to improve operational efficiency. Lead Scaled Agile (SAFe) practices, facilitating Program Increment (PI) Planning, Sprint Planning, and Agile ceremonies, ensuring iterative delivery of enterprise data capabilities. Collaborate with business stakeholders, product teams, and technology leaders to align data architecture strategies with organizational goals. Act as a trusted advisor on emerging data technologies and trends, ensuring that the enterprise adopts cutting-edge data solutions that provide competitive advantage and long-term scalability. Must-Have Skills: Experience in data architecture, enterprise data management, and cloud-based analytics solutions. Well versed in domain of Biotech/Pharma industry and has been instrumental in solving complex problems for them using data strategy. Expertise in Databricks, cloud-native data platforms, and distributed computing frameworks. Strong proficiency in modern data modeling techniques, including dimensional modeling, NoSQL, and data virtualization. Experience designing high-performance ETL/ELT pipelines and real-time data processing solutions. Deep understanding of data governance, security, metadata management, and access control frameworks. Hands-on experience with CI/CD for data solutions, DataOps automation, and infrastructure as code (IaC). Proven ability to collaborate with cross-functional teams, including business executives, data engineers, and analytics teams, to drive successful data initiatives. Strong problem-solving, strategic thinking, and technical leadership skills. Experienced with SQL/NOSQL database, vector database for large language models Experienced with data modeling and performance tuning for both OLAP and OLTP databases Experienced with Apache Spark, Apache Airflow Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops Good-to-Have Skills: Experience with Data Mesh architectures and federated data governance models. Certification in cloud data platforms or enterprise architecture frameworks. Knowledge of AI/ML pipeline integration within enterprise data architectures. Familiarity with BI & analytics platforms for enabling self-service analytics and enterprise reporting. Education and Professional Certifications 9 to 12 years of experience in Computer Science, IT or related field AWS Certified Data Engineer preferred Databricks Certificate preferred 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. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills.

We are seeking a detail-oriented and proactive Consultants to manage, track, and extract critical metadata from multiple contract types, including Merchant Service Agreements, Enterprise Banking Contracts, and Vendor Agreements. This role will be pivotal in organizing, linking, and extracting data from various formats (including OCR-based documents), while also managing contract lifecycles and addendums. Key Responsibilities: Contract Handling: Review and manage Merchant Service Agreements Analyze Banking Contracts , primarily in OCR (Optical Character Recognition) formats, ensuring data accuracy and completeness. Oversee Vendor Contracts , ensuring they align with internal policies and standards. Metadata Extraction & Management: Addendum Tracking & Linkage: Identify and link all contract addendums to their parent agreements to maintain contractual integrity. Ensure that updates and modifications are tracked and documented appropriately.

Req ID: 323226 We are currently seeking a Digital Solution Architect Sr. Advisor to join our team in Bengaluru, India, Karntaka (IN-KA), India (IN). Key Responsibilities: Design data platform architectures (data lakes, lakehouses, DWH) using modern cloud-native tools (e.g., Databricks, Snowflake, BigQuery, Synapse, Redshift). Architect data ingestion, transformation, and consumption pipelines using batch and streaming methods. Enable real-time analytics and machine learning through scalable and modular data frameworks. Define data governance models, metadata management, lineage tracking, and access controls. Collaborate with AI/ML, application, and business teams to identify high-impact use cases and optimize data usage. Lead modernization initiatives from legacy data warehouses to cloud-native and distributed architectures. Enforce data quality and observability practices for mission-critical workloads. Required Skills: 10+ years in data architecture, with strong grounding in modern data platforms and pipelines. Deep knowledge of SQL/NoSQL, Spark, Delta Lake, Kafka, ETL/ELT frameworks. Hands-on experience with cloud data platforms (AWS, Azure, GCP). Understanding of data privacy, security, lineage, and compliance (GDPR, HIPAA, etc.). Experience implementing data mesh/data fabric concepts is a plus. Expertise in technical solutions writing and presenting using tools such as Word, PowerPoint, Excel, Visio etc. High level of executive presence to be able to articulate the solutions to CXO level executives. Preferred Qualifications: Certifications in Snowflake, Databricks, or cloud-native data platforms. Exposure to AI/ML data pipelines, MLOps, and real-time data applications. Familiarity with data visualization and BI tools (Power BI, Tableau, Looker, etc.).

Role Purpose The purpose of the role is to define and develop Enterprise Data Structure along with Data Warehouse, Master Data, Integration and transaction processing with maintaining and strengthening the modelling standards and business information. Do 1. Define and Develop Data Architecture that aids organization and clients in new/ existing deals a. Partnering with business leadership (adopting the rationalization of the data value chain) to provide strategic, information-based recommendations to maximize the value of data and information assets, and protect the organization from disruptions while also embracing innovation b. Assess the benefits and risks of data by using tools such as business capability models to create an data-centric view to quickly visualize what data matters most to the organization, based on the defined business strategy c. Create data strategy and road maps for the Reference Data Architecture as required by the clients d. Engage all the stakeholders to implement data governance models and ensure that the implementation is done based on every change request e. Ensure that the data storage and database technologies are supported by the data management and infrastructure of the enterprise f. Develop, communicate, support and monitor compliance with Data Modelling standards g. Oversee and monitor all frameworks to manage data across organization h. Provide insights for database storage and platform for ease of use and least manual work i. Collaborate with vendors to ensure integrity, objectives and system configuration j. Collaborate with functional & technical teams and clients to understand the implications of data architecture and maximize the value of information across the organization k. Presenting data repository, objects, source systems along with data scenarios for the front end and back end usage l. Define high-level data migration plans to transition the data from source to target system/ application addressing the gaps between the current and future state, typically in sync with the IT budgeting or other capital planning processes m. Knowledge of all the Data service provider platforms and ensure end to end view. n. Oversight all the data standards/ reference/ papers for proper governance o. Promote, guard and guide the organization towards common semantics and the proper use of metadata p. Collecting, aggregating, matching, consolidating, quality-assuring, persisting and distributing such data throughout an organization to ensure a common understanding, consistency, accuracy and control q. Provide solution of RFPs received from clients and ensure overall implementation assurance i. Develop a direction to manage the portfolio of all the databases including systems, shared infrastructure services in order to better match business outcome objectives ii. Analyse technology environment, enterprise specifics, client requirements to set a collaboration solution for the big/small data iii. Provide technical leadership to the implementation of custom solutions through thoughtful use of modern technology iv. Define and understand current issues and problems and identify improvements v. Evaluate and recommend solutions to integrate with overall technology ecosystem keeping consistency throughout vi. Understand the root cause problem in integrating business and product units vii. Validate the solution/ prototype from technology, cost structure and customer differentiation point of view viii. Collaborating with sales and delivery leadership teams to identify future needs and requirements ix. Tracks industry and application trends and relates these to planning current and future IT needs 2. Building enterprise technology environment for data architecture management a. Develop, maintain and implement standard patterns for data layers, data stores, data hub & lake and data management processes b. Evaluate all the implemented systems to determine their viability in terms of cost effectiveness c. Collect all the structural and non-structural data from different places integrate all the data in one database form d. Work through every stage of data processing: analysing, creating, physical data model designs, solutions and reports e. Build the enterprise conceptual and logical data models for analytics, operational and data mart structures in accordance with industry best practices f. Implement the best security practices across all the data bases based on the accessibility and technology g. Strong understanding of activities within primary discipline such as Master Data Management (MDM), Metadata Management and Data Governance (DG) h. Demonstrate strong experience in Conceptual, Logical and physical database architectures, design patterns, best practices and programming techniques around relational data modelling and data integration 3. Enable Delivery Teams by providing optimal delivery solutions/ frameworks a. Build and maintain relationships with delivery and practice leadership teams and other key stakeholders to become a trusted advisor b. Define database physical structure, functional capabilities, security, back-up and recovery specifications c. Develops and establishes relevant technical, business process and overall support metrics (KPI/SLA) to drive results d. Monitor system capabilities and performance by performing tests and configurations e. Integrate new solutions and troubleshoot previously occurred errors f. Manages multiple projects and accurately reports the status of all major assignments while adhering to all project management standards g. Identify technical, process, structural risks and prepare a risk mitigation plan for all the projects h. Ensure quality assurance of all the architecture or design decisions and provides technical mitigation support to the delivery teams i. Recommend tools for reuse, automation for improved productivity and reduced cycle times j. Help the support and integration team for better efficiency and client experience for ease of use by using AI methods. k. Develops trust and builds effective working relationships through respectful, collaborative engagement across individual product teams l. Ensures architecture principles and standards are consistently applied to all the projects m. Ensure optimal Client Engagement i. Support pre-sales team while presenting the entire solution design and its principles to the client ii. Negotiate, manage and coordinate with the client teams to ensure all requirements are met iii. Demonstrate thought leadership with strong technical capability in front of the client to win the confidence and act as a trusted advisor Mandatory Skills: Prophecy.AI.

We are looking for a skilled Data Management Specialist with hands-on experience in Informatica Intelligent Data Management Cloud (IDMC), SQL, Metadata management, and Master & Reference Data Management (MDM/RDM).

Dear Candidate, We are hiring a Data Quality Analyst to ensure the accuracy, integrity, and consistency of enterprise data assets. This role supports data-driven decision-making through validation, profiling, and quality improvement initiatives. Key Responsibilities: Monitor, measure, and report on data quality metrics. Identify data anomalies and work with teams to resolve issues. Perform data profiling and root cause analysis. Design and execute data validation tests and quality rules. Collaborate with data stewards, engineers, and business teams. Required Skills & Qualifications: Strong SQL skills and experience with data profiling tools. Familiarity with data governance and MDM concepts. Experience with ETL processes and reporting platforms. Analytical mindset with attention to detail. Knowledge of tools like Talend, Informatica, or Collibra is a plus. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Delivery Manager Integra Technologies

Wipro Limited (NYSE:WIT, BSE:507685, NSE:WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com. About The Role : Role Purpose The purpose of the role is to define and develop Enterprise Data Structure along with Data Warehouse, Master Data, Integration and transaction processing with maintaining and strengthening the modelling standards and business information. Do 1. Define and Develop Data Architecture that aids organization and clients in new/ existing deals a. Partnering with business leadership (adopting the rationalization of the data value chain) to provide strategic, information-based recommendations to maximize the value of data and information assets, and protect the organization from disruptions while also embracing innovation b. Assess the benefits and risks of data by using tools such as business capability models to create an data-centric view to quickly visualize what data matters most to the organization, based on the defined business strategy c. Create data strategy and road maps for the Reference Data Architecture as required by the clients d. Engage all the stakeholders to implement data governance models and ensure that the implementation is done based on every change request e. Ensure that the data storage and database technologies are supported by the data management and infrastructure of the enterprise f. Develop, communicate, support and monitor compliance with Data Modelling standards g. Oversee and monitor all frameworks to manage data across organization h. Provide insights for database storage and platform for ease of use and least manual work i. Collaborate with vendors to ensure integrity, objectives and system configuration j. Collaborate with functional & technical teams and clients to understand the implications of data architecture and maximize the value of information across the organization k. Presenting data repository, objects, source systems along with data scenarios for the front end and back end usage l. Define high-level data migration plans to transition the data from source to target system/ application addressing the gaps between the current and future state, typically in sync with the IT budgeting or other capital planning processes m. Knowledge of all the Data service provider platforms and ensure end to end view. n. Oversight all the data standards/ reference/ papers for proper governance o. Promote, guard and guide the organization towards common semantics and the proper use of metadata p. Collecting, aggregating, matching, consolidating, quality-assuring, persisting and distributing such data throughout an organization to ensure a common understanding, consistency, accuracy and control q. Provide solution of RFPs received from clients and ensure overall implementation assurance i. Develop a direction to manage the portfolio of all the databases including systems, shared infrastructure services in order to better match business outcome objectives ii. Analyse technology environment, enterprise specifics, client requirements to set a collaboration solution for the big/small data iii. Provide technical leadership to the implementation of custom solutions through thoughtful use of modern technology iv. Define and understand current issues and problems and identify improvements v. Evaluate and recommend solutions to integrate with overall technology ecosystem keeping consistency throughout vi. Understand the root cause problem in integrating business and product units vii. Validate the solution/ prototype from technology, cost structure and customer differentiation point of view viii. Collaborating with sales and delivery leadership teams to identify future needs and requirements ix. Tracks industry and application trends and relates these to planning current and future IT needs 2. Building enterprise technology environment for data architecture management a. Develop, maintain and implement standard patterns for data layers, data stores, data hub & lake and data management processes b. Evaluate all the implemented systems to determine their viability in terms of cost effectiveness c. Collect all the structural and non-structural data from different places integrate all the data in one database form d. Work through every stage of data processing:analysing, creating, physical data model designs, solutions and reports e. Build the enterprise conceptual and logical data models for analytics, operational and data mart structures in accordance with industry best practices f. Implement the best security practices across all the data bases based on the accessibility and technology g. Strong understanding of activities within primary discipline such as Master Data Management (MDM), Metadata Management and Data Governance (DG) h. Demonstrate strong experience in Conceptual, Logical and physical database architectures, design patterns, best practices and programming techniques around relational data modelling and data integration 3. Enable Delivery Teams by providing optimal delivery solutions/ frameworks a. Build and maintain relationships with delivery and practice leadership teams and other key stakeholders to become a trusted advisor b. Define database physical structure, functional capabilities, security, back-up and recovery specifications c. Develops and establishes relevant technical, business process and overall support metrics (KPI/SLA) to drive results d. Monitor system capabilities and performance by performing tests and configurations e. Integrate new solutions and troubleshoot previously occurred errors f. Manages multiple projects and accurately reports the status of all major assignments while adhering to all project management standards g. Identify technical, process, structural risks and prepare a risk mitigation plan for all the projects h. Ensure quality assurance of all the architecture or design decisions and provides technical mitigation support to the delivery teams i. Recommend tools for reuse, automation for improved productivity and reduced cycle times j. Help the support and integration team for better efficiency and client experience for ease of use by using AI methods. k. Develops trust and builds effective working relationships through respectful, collaborative engagement across individual product teams l. Ensures architecture principles and standards are consistently applied to all the projects m. Ensure optimal Client Engagement i. Support pre-sales team while presenting the entire solution design and its principles to the client ii. Negotiate, manage and coordinate with the client teams to ensure all requirements are met iii. Demonstrate thought leadership with strong technical capability in front of the client to win the confidence and act as a trusted advisor Reinvent your world.We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention. Come to Wipro. Realize your ambitions. Applications from people with disabilities are explicitly welcome.

Job : Data Governance/Data Management About Us Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount . With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. WHY JOIN CAPCO? You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry. MAKE AN IMPACT Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services. #BEYOURSELFATWORK Capco has a tolerant, open culture that values diversity, inclusivity, and creativity. CAREER ADVANCEMENT With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands. DIVERSITY & INCLUSION We believe that diversity of people and perspective gives us a competitive advantage. Job : Data Governance/Data Management Location - Bangalore Exp - 4+ years Key Skills : Data Governance/Data Management (Mandatory) , Collibra / Informatica IDQ Domain : BFSI Responsibilities : Support the business in driving Data Governance principles according to the regulatory reporting requirements like BCBS 239 / CCAR /Liquidity. Work with the Business Owners to identify and understand data used for a business process and create a Business Glossary and Metadata in Collibra. Work with Data Architecture team to identify and document the physical data elements in order to build data quality controls. Document data lineage for a business concept. Issue Management related to Data Quality controls / Data Lineage / Data policies and procedures Role Requirements: Understanding/ experience of Collibra or other data governance tools. Working experience in a Data Governance role. Understanding of banking regulation's risk and controls. Example BCBS 239 / CCAR / GDPR / Liquidity

About TELUS Digital TELUS Digital (NYSE and TSX: TIXT) designs, builds, and delivers next-generation digital solutions to enhance the customer experience (CX) for global and disruptive brands. The companys services support the full lifecycle of its clients digital transformation journeys and enable them to more quickly embrace next-generation digital technologies to deliver better business outcomes. TELUS Digitals integrated solutions and capabilities span digital strategy, innovation, consulting and design, digital transformation and IT lifecycle solutions, data annotation, and intelligent automation, and omnichannel CX solutions that include content moderation, trust and safety solutions, and other managed solutions. Fueling all stages of company growth, TELUS Digital partners with brands across high-growth industry verticals, including tech and games, communications and media, eCommerce and fintech, healthcare, and travel and hospitality. Learn more at: telusinternational.com. Position Overview: We have an ambitious Enterprise Data Office and are building a class-leading data team that works to solve complex business challenges and provide insights to improve our business and customer experience. To enhance the team, we are looking for an innovative and enterprising Data Governance Engineer who plays a critical role in shaping and implementing our enterprise- wide data governance and data management roadmap and strategy. The Data Governance Engineer will focus their work on 'data is an asset' thinking across the enterprise, integrating the Data Governance tools implementations of Collibra Data Intelligence Platform, Collibra Data Quality, Google Cloud Data Related Tools, and Informatica MDM/RDM. This person will work with internal partners and developers to brainstorm and evaluate technical solutions, product integration opportunities and demonstrations. This role requires creative thinking, a deep curiosity and understanding of data models and usage, as well as empathy for partner/client challenges and pain points. Essential Responsibilities:

Locations - Pune/Bangalore/Hyderabad/Indore Contract duration- 6 months Responsibilities Be responsible for the development of the conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lakes on target platforms. Implement business and IT data requirements through new data strategies and designs across all data platforms (relational & dimensional - MUST and NoSQL-optional) and data tools (reporting, visualization, analytics, and machine learning). Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models. Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization. Hands-on modeling, design, configuration, installation, performance tuning, and sandbox POC. Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks. Must have Payments Background Skills Hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols). Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-center contexts required. Good knowledge of metadata management, data modeling, and related tools (Erwin or ER Studio or others) required. Experience in team management, communication, and presentation. Experience with Erwin, Visio or any other relevant tool.

We are hiring for a leading Insurance Consulting organisation for Data Strategy & Governance role Exp: 4 to 6 yyrs Location : BangalorePune Responsibility: Develop and Drive Data Capability Maturity Assessment, Data & Analytics Operating Model & Data Governance exercises for clients Managing Critical Data Elements (CDEs) and coordinating with Finance Data Stewards Overseeing data quality standards and governance implementation Establish processes around effective data management ensuring Data Quality & Governance standards as well as roles for Data Stewards

Dear Candidate, We are looking for a Data Governance Specialist to establish and maintain data governance policies, ensuring data quality, compliance, and responsible usage across the organization. Key Responsibilities: Define and enforce data governance policies and standards. Work with data owners and stewards to improve data quality. Monitor compliance with data privacy regulations (GDPR, HIPAA, etc.). Support metadata management, data lineage, and cataloging initiatives. Promote data literacy across departments. Required Skills & Qualifications: Experience with data governance tools (Collibra, Alation, Informatica). Knowledge of regulatory frameworks and data privacy laws. Strong analytical and documentation skills. Understanding of data architecture, MDM, and data stewardship. Excellent stakeholder management and communication skills. Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Srinivasa Reddy Kandi Delivery Manager Integra Technologies

Job Summary: Cummins is seeking a skilled Data Engineer to support the development, maintenance, and optimization of our enterprise data and analytics platform. This role involves hands-on experience in software development , ETL processes , and data warehousing , with strong exposure to tools like Snowflake , OBIEE , and Power BI . The engineer will collaborate with cross-functional teams, transforming data into actionable insights that enable business agility and scale. Please NoteWhile the role is categorized as remote, it will follow a hybrid work model based out of our Pune office . Key Responsibilities: Design, develop, and maintain ETL pipelines using Snowflake and related data transformation tools. Build and automate data integration workflows that extract, transform, and load data from various sources including Oracle EBS and other enterprise systems. Analyze, monitor, and troubleshoot data quality and integrity issues using standardized tools and methods. Develop and maintain dashboards and reports using OBIEE , Power BI , and other visualization tools for business stakeholders. Work with IT and Business teams to gather reporting requirements and translate them into scalable technical solutions. Participate in data modeling and storage architecture using star and snowflake schema designs. Contribute to the implementation of data governance , metadata management , and access control mechanisms . Maintain documentation for solutions and participate in testing and validation activities. Support migration and replication of data using tools such as Qlik Replicate and contribute to cloud-based data architecture . Apply agile and DevOps methodologies to continuously improve data delivery and quality assurance processes. Why Join Cummins? Opportunity to work with a global leader in power solutions and digital transformation. Be part of a collaborative and inclusive team culture. Access to cutting-edge data platforms and tools. Exposure to enterprise-scale data challenges and finance domain expertise . Drive impact through data innovation and process improvement . Competencies Data Extraction & Transformation - Ability to perform ETL activities from varied sources with high data accuracy. Programming - Capable of writing and testing efficient code using industry standards and version control systems. Data Quality Management - Detect and correct data issues for better decision-making. Solution Documentation - Clearly document processes, models, and code for reuse and collaboration. Solution Validation - Test and validate changes or solutions based on customer requirements. Problem Solving - Address technical challenges systematically to ensure effective resolution and prevention. Customer Focus - Understand business requirements and deliver user-centric data solutions. Communication & Collaboration - Work effectively across teams to meet shared goals. Values Differences - Promote inclusion by valuing diverse perspectives and backgrounds. Education, Licenses, Certifications Bachelor s or Master s degree in Computer Science, Information Systems, Data Engineering, or a related technical discipline. Certifications in data engineering or relevant tools (Snowflake, Power BI, etc.) are a plus. Experience Must have skills 5-7 years of experience in data engineering or software development , preferably within a finance or enterprise IT environment. Proficient in ETL tools , SQL , and data warehouse development . Proficient in Snowflake , Power BI , and OBIEE reporting platforms. Must have worked in implementation using these tools and technologies. Strong understanding of data warehousing principles , including schema design (star/snowflake), ER modeling, and relational databases. Working knowledge of Oracle databases and Oracle EBS structures. Preferred Skills: Experience with Qlik Replicate , data replication , or data migration tools. Familiarity with data governance , data quality frameworks , and metadata management . Exposure to cloud-based architectures, Big Data platforms (e.g., Spark, Hive, Kafka), and distributed storage systems (e.g., HBase, MongoDB). Understanding of agile methodologies (Scrum, Kanban) and DevOps practices for continuous delivery and improvement.

Overview As an Analyst, Data Modeler, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analysing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data Modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premises data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, Data Bricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications Bachelors degree required in Computer Science, Data Management/Analytics/Science, Information Systems, Software Engineering or related Technology Discipline. 5+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or Snowflake. Experience with version control systems like GitHub and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including Dev Ops and Data Ops concepts. Familiarity with business intelligence tools (such as Power BI). Excellent verbal and written communication and collaboration skills.

Overview Job Overview: As an Analyst, Data Modeling , your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics . The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities : Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper management: business and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levels: low-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications : 5+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operatinghighly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI).

Overview As Senior Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper management: business and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levels: low-latency, relational, and unstructured data stores; analytical and data lakes; data str/cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 8+ years of overall technology experience that includes at least 4+ years of data modeling and systems architecture. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI).

Overview As an Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper management: business and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levels: low-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 5+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as Power BI).

Role Description: You will play a key role in the implementation and adoption of the data governance framework which will modernize Amgen's data ecosystem, positioning Amgen as a leader in biopharma innovation. This role leverages state-of-the-art technologies, including Generative AI, Machine Learning, and integrated data. This role involves working closely with business stakeholders and data analysts to ensure implementation and adoption of the data governance framework. You will collaborate with the Product Owner and other Business Analysts to ensure operational support and excellence from the team. Roles & Responsibilities: Responsible for the data governance and data management framework implementation for the Research domain of the biopharma lifecycle. Contribute to the operationalization of the Enterprise data governance framework and aligning broader stakeholder community with their data governance needs, including data quality, data access controls, compliance with privacy and security regulations, foundational master data management, data sharing, communication and change management. Works with Enterprise MDM and Reference Data to enforce standards and data reusability. Contribute to the cross functional alignment in his/her domain(s) of expertise to ensure adherence to Data Governance principles. Maintain documentation on data definitions, data standards, data flows, legacy data structures / hierarchies, common data models, data harmonization etc. for assigned domains. Partner with business teams to identify compliance requirements with data privacy, security, and regulatory policies for the assigned domains Jointly with Technology teams, business functions, and enterprise teams (e.g., MDM, Enterprise Data Fabric, etc.) define the specifications shaping the development and implementation of data foundations. Build strong relationships with key business leaders and partners to ensure their needs are met Functional Skills: Must-Have Functional Skills: Technical skills with knowledge of Pharma processes with specialization in the Research domain of the biopharma lifecycle. General knowledge of data management, common data models, metadata management, data quality, master data management, data stewardship, data protection, etc. Experience with data products development life cycle, including the enablement of data dictionaries, business glossary to increase data products reusability and data literacy. Customer-focused with excellent written and verbal communication skills who can confidently work with internal Amgen business stakeholders and external service partners on business process and technology topics Experience of working with or supporting systems used to data governance framework. E.g. Collibra, Alation Excellent problem-solving skills and committed attention to detail in finding solutions Good-to-Have Functional Skills: Experience with Agile software development methodologies (Scrum) Proficiency in data analysis and quality tools (e.g., SQL, Excel, Python, or SAS) Soft Skills: Highly organized and able to work under minimal supervision Excellent analytical and assessment skills Ability to work effectively with global, virtual teams Ability to manage multiple priorities successfully Team-oriented, with a focus on achieving team goals Ambitious to further develop their skills and career Ability to build business relationships and understand end-to-end data use and needs. Excellent interpersonal skills (team player). People management skills either in matrix or direct line function. Strong verbal and written communication skills High degree of initiative and self-motivation. Good presentation and public speaking skills. Strong attention to detail, quality, time management and customer focus. Basic Qualifications: Bachelors degree and 3 to 5 years of Life Science/Biotechnology/Pharmacology/Information Systems experience OR Diploma and 7 to 9 years of Life Science/Biotechnology/Pharmacology/ Information Systems experience

Job Information Job Opening ID ZR_2385_JOB Date Opened 23/10/2024 Industry IT Services Job Type Work Experience 8-12 years Job Title Data modeller City Bangalore South Province Karnataka Country India Postal Code 560066 Number of Positions 1 Locations - Pune/Bangalore/Hyderabad/Indore Contract duration- 6 months Responsibilities Be responsible for the development of the conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lakes on target platforms. Implement business and IT data requirements through new data strategies and designs across all data platforms (relational & dimensional - MUST and NoSQL-optional) and data tools (reporting, visualization, analytics, and machine learning). Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models. Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization. Hands-on modeling, design, configuration, installation, performance tuning, and sandbox POC. Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks. Must have Payments Background Skills Hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols). Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-center contexts required. Good knowledge of metadata management, data modeling, and related tools (Erwin or ER Studio or others) required. Experience in team management, communication, and presentation. Experience with Erwin, Visio or any other relevant tool. check(event) ; career-website-detail-template-2 => apply(record.id,meta)" mousedown="lyte-button => check(event)" final-style="background-color:#2B39C2;border-color:#2B39C2;color:white;" final-class="lyte-button lyteBackgroundColorBtn lyteSuccess" lyte-rendered=""> I'm interested