Senior Data Lead (3 Months Fixed Term Contract)

IFS is a billion-dollar revenue company with 7000+ employees on all continents. Our leading AI technology is the backbone of our award-winning enterprise software solutions, enabling our customers to be their best when it really matters–at the Moment of Service™. Our commitment to internal AI adoption has allowed us to stay at the forefront of technological advancements, ensuring our colleagues can unlock their creativity and productivity, and our solutions are always cutting-edge. At IFS, we’re flexible, we’re innovative, and we’re focused not only on how we can engage with our customers but on how we can make a real change and have a worldwide impact. We help solve some of society’s greatest challenges, fostering a better future through our agility, collaboration, and trust. We celebrate diversity and understand our responsibility to reflect the diverse world we work in. We are committed to promoting an inclusive workforce that fully represents the many different cultures, backgrounds, and viewpoints of our customers, our partners, and our communities. As a truly international company serving people from around the globe, we realize that our success is tantamount to the respect we have for those different points of view. By joining our team, you will have the opportunity to be part of a global, diverse environment; you will be joining a winning team with a commitment to sustainability; and a company where we get things done so that you can make a positive impact on the world. We’re looking for innovative and original thinkers to work in an environment where you can #MakeYourMoment so that we can help others make theirs. With the power of our AI-driven solutions, we empower our team to change the status quo and make a real difference. If you want to change the status quo, we’ll help you make your moment. Join Team Purple. Join IFS. Summary We are seeking an experienced Senior Data Lead with strong expertise in CRM data integration, analytics solutions, enterprise data architecture and data governance to lead the implementation of HubSpot data into the IFS Enterprise Data Lake. The ideal candidate will be responsible for translating business requirements into scalable data solutions, enabling trusted analytics across sales, marketing, customer engagement and business performance domains. This role requires strong experience in HubSpot data structures, data modeling, data integration, metadata management, data quality and analytics platforms. The Data lead will collaborate closely with business stakeholders, marketing and sales teams, data engineers, analytics teams and enterprise architect to deliver secure, scalable and high-quality data solutions that support reporting, dashboarding and advanced analytics initiatives. The Senior Data lead will design and be responsible for the implementation of scalable, integrated data solutions across the L2O landscape. Working closely with Systems Integrators (SI), IFS, Data & Analytics teams, PMO and Sales stakeholders, the role ensures optimal data integration architecture, high data quality and ensure minimal impact on the data model. The engagement will look at the existing data models built from THOR/ IFS Cloud & provide a least minimal impact solution with data sourced from Hubspot. It will provide data leadership across the full L2O landscape, including HubSpot, DealHub, THOR/IFS Cloud, Power BI / Microsoft Fabric and related data sources. The Senior Data Architect will provide documentation and support the data engineer with the implementation. The successful candidate will work under the direction and guidance of the Senior Director, Data & Analytics, who will provide strategic oversight, business priorities and ensure successful project delivery. The role will also work closely with the Senior Technical Manager, Data & Analytics on solution architecture, technical design, implementation planning, data integration activities and adherence to enterprise data standards. This collaborative leadership structure is intended to provide clear direction, remove delivery obstacles and enable the Data Lead to focus on delivering a successful HubSpot analytics solution within the IFS Enterprise Data Lake. Key L2O Scope Covered by the Role Architect & Design Hubspot data for Analytics into Data lake Assess and document HubSpot data sources, entities, relationships and business requirements for analytics consumption. Design scalable data architecture and ingestion frameworks to extract HubSpot data into the enterprise data lake. Define data models, schemas and storage strategies to support reporting, analytics and downstream impact. Establish data mapping, transformation and enrichment rules to align HubSpot data with enterprise standards. Implement data quality, validation and governance controls to ensure accuracy, consistency and compliance. Design incremental data integration patterns to support timely analytics and operational reporting. Develop metadata, lineage and documentation standards for HubSpot data assets within the data lake ecosystem. Collaborate with business stakeholders, analytics teams and data engineers to ensure minimal reporting impact during the transition from the existing CRM platform (THOR/ IFS Cloud) to HubSpot. Optimize data pipelines and storage structures for performance, scalability and cost efficiency. Provide architecture recommendations and best practices for future expansion of customer, marketing, sales and service analytics. Create Functional Requirement Document (FRD) Conduct stakeholder workshops and requirement gathering sessions to capture business, functional and reporting needs. Document business objectives, scope, assumptions, dependencies and success criteria for the HubSpot analytics solution. Define functional requirements for data ingestion, transformation, storage and consumption within the fabric/ data lake environment. Capture source-to-target mapping requirements, including business rules, data definitions and transformation logic. Document analytical use cases, KPIs, metrics, dashboards and reporting requirements. Define data quality, validation, reconciliation and exception-handling requirements. Capture security, privacy, compliance and data governance requirements. Document user roles, access controls and data consumption requirements for business and technical stakeholders. Develop process flows, data flow diagrams and functional specifications to support implementation. Facilitate requirement reviews, stakeholder sign-off, and change management throughout the project lifecycle. Provide traceability between business requirements, functional requirements and solution design artifacts. Implementation of Data from HubSpot into IFS enterprise Data Lake Assist the data engineer with configuring and implementing secure data extraction processes from HubSpot using APIs, connectors or integration services. Assist the data engineer with development and deployment of automated data ingestion pipelines to load HubSpot data into the IFS Enterprise Data Lake. Assist the data engineer with Implementation of data transformation, cleansing and standardization processes in accordance with approved business rules and data models. Key Deliverables Ref Deliverable Description D1 Architecture & Design of Hubspot data for Analytics into Data lake Data architecture document Documentation of ingestion frameworks to extract HubSpot data into the enterprise data lake Document HubSpot data sources, entities, relationships and business requirements for analytics consumption. D2 Functional Requirement Document (FRD) Document business objectives, scope, assumptions, dependencies and success criteria for the HubSpot analytics solution. Define functional requirements for data ingestion, transformation, storage and consumption within the fabric/ data lake environment. D3 Data pipelines, data quality dashboards Data pipelines running with incremental data load. Data quality dashboards Data lineage implementation for HubSpot data Data catalogue implementation for HubSpot data Essential Experience 5-8 years of experience in data architecture, data engineering or enterprise data management. 3+ years of hands-on experience with Microsoft Fabric and Azure data platforms. Microsoft Fabric AI Capabilities Azure AI Services Azure Machine Learning Generative AI Strong experience in enterprise data governance and metadata management. Proven experience designing enterprise-scale data models and analytics platforms. Strong data management skills Good understanding of Star Schema based framework, Data warehouse and Data Mart and Materialized View Good understanding of database concepts like normalization, joins, changing dimensions etc.. Good understanding of relational and non-relational database management systems Experience in CRM, CPQ, sales, commercial, ERP or quote-to-cash / lead-to-order solutions. Strong stakeholder management, written communication and evidence-based reporting skills. University degree in Computer Science, Information Systems, Engineering, Business Systems or equivalent practical experience; fluency in English. Highly Beneficial Experience Experience with HubSpot, DealHub, Salesforce, Dynamics or similar CRM / sales platforms. Experience with CPQ platforms, quotation/pricing flows, approval workflows and DAR-like governance processes. Experience with ERP integration, preferably IFS Cloud / THOR, SAP, Oracle or NetSuite. Experience with Azure BI technology (Fabric, Synapse, Power BI, Azure SQL, SSIS, SSAS, Purview, OneLake, ADF) Technical Skills Fabric, Synapse, Power BI, Azure SQL, SSIS, SSAS, Purview, OneLake, ADF Management tools such as Jira, Azure DevOps. Collaboration tools such as Confluence, SharePoint, Teams or equivalent. Business and Process Knowledge Lead-to-Order / Lead-to-Cash process concepts. Lead, account, contact, opportunity, quote, contract and order data flows. Data quality and master data dependencies. Leadership and Behavioural Competencies Lead testing across multiple teams without direct line management authority. Be structured, pragmatic and delivery-focused. Communicate clearly with both technical teams and business stakeholders. Challenge incomplete requirements, unclear ownership and insufficient test evidence. Escalate risks early and professionally. Maintain control under delivery pressure. Separate critical go-live issues from lower-priority improvements. Drive accountability across vendors, IT and business. Build confidence with senior stakeholders through clear reporting and evidence. Operate independently while staying aligned with programme governance. Education and Certifications Essential University degree in Computer Science, Information Systems, Engineering, Business Systems or equivalent practical experience. Fluency in English, written and verbal. Proven experience in test leadership roles. Highly Beneficial Fabric Data Engineer. We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles, while also valuing inclusive workplace experiences. By fostering a sense of community, we drive innovation, strengthen connections, and nurture belonging. Our commitment ensures you can work in a way that suits you best, while also engaging with colleagues to share ideas and build meaningful relationships.