Summary
We are seeking an experienced Senior Data Engineer with strong expertise in CRM data integration, analytics solutions to implement data pipelines for ingesting HubSpot data into the IFS Enterprise Data Lake and model the analytical solution for report & AI consumption.
This role requires strong experience in HubSpot data structures, data modeling, data integration and analytics platforms. The Data Engineer will collaborate closely with Data Lead, 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 Engineer will 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 pipelines, 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.
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.
Key L2O Scope Covered by the Role
Implement HubSpot data pipelines into the Data Lake
- Implement secure data extraction processes from HubSpot using APIs, connectors or integration services.
- Development and deployment of automated data ingestion pipelines to load HubSpot data into the IFS Enterprise Data Lake.
- Implementation of data transformation, cleansing and standardization processes in accordance with approved business rules and data models.
- 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.
Create Data Models for Analytics & AI
- Create data models to support reporting, analytics with minimal downstream impact.
- Be involved in stakeholder workshops and requirement gathering sessions to capture business, functional and reporting needs.
- Document data pipelines, schema and transformations
- 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.
Overall Required Competence
Essential Experience
- 5-8 years of experience in data engineering.
- 3+ years of hands-on experience with Microsoft Fabric and Azure data platforms.
- Microsoft Fabric AI Capabilities
- Azure AI Services
- Azure Machine Learning
- 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 / Engineer-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
- Engineer-to-Order / Engineer-to-Cash process concepts.
- Engineer, account, contact, opportunity, quote, contract and order data flows.
- Data quality and master data dependencies.
Education and Certifications
Essential
- University degree in Computer Science, Information Systems, Engineering, Business Systems or equivalent practical experience.
- Fluency in English, written and verbal.
Highly Beneficial
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.