Data Architect - Corporate Functions

Purpose

The Data Architect Corporate Functions leads high-priority data initiatives, leveraging Databricks to solve complex data challenges for data scientists, AI agents and data consumers. Acting as the bridge between functional data experts and technical data engineers, this role translates business needs into robust, scalable, and well-governed data solutions.

This position is accountable for the end-to-end design, deployment, and user experience of data and analytics products supporting Corporate Functions (Finance, HR, Indirect Procurement, Legal, Facility Management, etc. ). The Data Architect owns the full data landscape for intelligent solutions delivered by IT&D teams, including architectural design, proof-of-concept implementation, and management of development, testing, and production environments.

As a key enabler in the Corporate Functions Data & AI journey, the Data Architect ensures data is interoperable, high-quality, well-governed, and hosted on the right platforms. The role works closely with the Central Data & Analytics Architecture team to align functional and enterprise-wide needs, ensure the right technologies are in place, and embed Corporate Functions within the organization s Data Mesh framework.

Accountabilities

• Solution Design for Corporate Functions:

  • Design and implement

    Databricks-centered

    data architectures and patterns to meet the needs of Finance, HR, Procurement, Legal, and other corporate functions.
  • Ensure solutions meet requirements for reporting, analytics, and AI/ML, while aligning with enterprise data and security standards.

• Domain & Data Product Architecture:

  • Architect data products and data domains within a Data Mesh framework, defining ownership, quality controls, and security measures for corporate function datasets.
  • Translate business requirements from corporate stakeholders into scalable, maintainable data designs.

• Data Modelling & Platform Build:

  • Lead the design of logical and physical data models for corporate function data warehouses and lakehouse environments.
  • Guide Data Engineers in implementing these models and building data pipelines.

• Leadership & Collaboration

  • Lead and mentor Data Engineers, SMEs, and external consultants working on corporate function data initiatives.
  • Work closely with business analysts, product owners, and governance teams to ensure solutions meet functional and compliance needs.

• Integration & Automation

  • Architect integration solutions using AWS Glue, Fivetran, and SnapLogic for both batch and real-time data flows.
  • Collaborate with platform teams to automate CI/CD for AWS-hosted data platform components.

• Migration & Modernization

  • Contribute to migration strategies from legacy corporate data platforms into the Data Mesh and lakehouse environments.

Professional Experience:

• 15+ years of overall professional experience, including:
  • 10+ years in architecting enterprise-scale data solutions.
  • 4+ years designing FAIR (Findable, Accessible, Interoperable, Reusable) data products optimized for AI consumption.
• Significant experience in corporate functional domains such as Finance, HR, Procurement, or Legal.

Technical Expertise:

• Data Platforms & Cloud:

  Deep expertise in Databricks and AWS (Redshift, S3, Glue, Lambda, EFS, RDS, Athena, EMR, Spark).

• Programming & Scripting:

  Proficient in Python and Linux Bash for automation, ETL, and orchestration.

• Integration & Tools:

  Skilled in Fivetran, SnapLogic, and collaboration platforms (Jira, Bitbucket, Confluence).

• Data Modelling:

  Strong capabilities in logical, physical, and dimensional modelling; optimization for both row-based and columnar environments.

• Architecture Best Practices:

  Ability to design solutions aligned with the AWS Well-Architected Framework and Databricks best practices across compute, storage, database, networking, security, governance, and ML service categories.

• Enterprise Systems:

  Experience integrating data from SAP ECC/S4, Ariba, Workday, and other corporate platforms.

• Multi-Cloud Awareness:

  Understanding of Azure and Google Cloud offerings for hybrid and multi-cloud strategies

Methodologies & Practices:

• Data Governance:

  Extensive experience implementing governance frameworks within Data Mesh architectures.

• AI-Ready Architectures:

  Proven ability to design data products and pipelines optimized for AI/ML consumption.

• Agile Delivery:

  Hands-on leadership in Scrum/Agile environments, including roles as Product Owner or Scrum Master.

• CI/CD & Automation:

  Skilled in designing and maintaining CI/CD pipelines for data solutions.

Key Competencies:

• Strategic Thinking & Problem Solving:

  Ability to analyse and simplify complex problems, articulate trade-offs for informed decision-making, and make appropriate recommendations.

• Collaboration & Influence:

  Excellence in collaboration, cross-functional expectation management, and influencing skills.

• Business Acumen:

  Ability to translate business requirements into databases, data warehouses, and data streams.

• Data Management:

  Experience in creating procedures to ensure data accuracy and accessibility; analysing, planning, and defining data architecture frameworks (including security, reference data, metadata, and master data); and creating and implementing data management processes and procedures.

• Stakeholder Engagement:

  Proven ability to collaborate with other teams within the organization to devise and implement data strategies, build models, and assess shareholder needs and goals.

• Innovation:

  Aptitude for researching data acquisition opportunities and developing application programming interfaces (APIs) to retrieve data.

• Communication:

  Excellent written, verbal, and meeting facilitation skills.

Bachelors or Masters degree in informatics, computer science, or a related Data & Analytics field.