Senior Data Lead (3 Months Fixed Term Contract)

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 e