Wella
Director, Data Delivery
Little Witcombe
Posted about 1 month ago
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Director, Data Delivery
Location: London
Reports to:
- Senior Director, Corporate Functions
- Head of Data & Analytics
Department: IT/Technology
About the Wella Company
Together, we enable individuals to look, feel, and be their true selves.
Wella Company is one of the world’s leading beauty companies, comprised of iconic brands such as:
- Wella Professionals
- Clairol
- OPI
- Nioxin
- ghd
With 6,000 employees globally and a presence in over 100 countries, Wella Company empowers its people to:
- Delight consumers
- Inspire beauty professionals
- Engage communities
- Drive sustainable growth
Visit www.wellacompany.com for more details.
The Role
The Director, Data Delivery is a strategic and execution-focused leader responsible for enabling Wella’s data-driven transformation through scalable, high-quality, and AI-ready data platforms. This role leads the delivery and operationalization of modern data solutions, ensuring enterprise data is:
- Accessible
- Governed
- Optimized for advanced analytics and AI use cases
Key Responsibilities
Data Platform Architecture, Delivery & Engineering Execution & Operations
- Own the end-to-end delivery of data solutions across Databricks & SAP, aligned with enterprise architecture principles.
- Oversee setup, configuration, and optimization of data environments for performance, scalability, and reliability.
- Drive implementation of scalable ingestion processes (batch and real-time), transformation pipelines, and curated data layers.
- Establish and enforce standards for coding, CI/CD, testing, and deployment across all data delivery teams.
- Ensure consistent implementation of MLOps & MLflow for model lifecycle management and reproducibility.
- Lead the Data Solution Architecture practice to maintain design integrity and enforce execution of data architecture patterns.
Vendor Delivery Management & Governance
- Lead delivery through third-party vendor squads, ensuring high-quality, timely, and cost-effective execution.
- Define clear delivery expectations, SLAs, KPIs, and acceptance criteria for all vendor teams.
- Hold vendors accountable for performance, quality, and governance standards.
- Establish governance frameworks (e.g., sprint reviews, delivery checkpoints) or performance tracking.
- Proactively manage delivery risks, issues, and dependencies to minimize business impact.
- Drive continuous improvement in vendor performance, productivity, and delivery outcomes.
Solution Delivery, Operations & Lifecycle Management
- Ensure end-to-end accountability for data product lifecycles (ingestion to consumption).
- Establish and manage disciplined release management, testing, and deployment practices.
- Maintain platform reliability, stability, and scalability across all data workloads.
- Optimize data processing performance and cost efficiency.
- Serve as the escalation point for delivery/operational issues relating to data pipelines and platforms.
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Data Governance, Quality & AI Readiness
- Establish and implement enterprise data governance standards and policies.
- Align with enterprise data governance via means of data classification standards.
- Drive data quality frameworks (monitoring, validation, remediation).
- Ensure AI-ready datasets through standardization, cleansing, and enrichment.
- Collaborate with governance, security, and compliance teams to meet regulatory and privacy requirements.
Business Engagement & Value Delivery
- Partner with business stakeholders to translate requirements into scalable data solutions.
- Enable advanced analytics, reporting, and AI initiatives via high-quality data.
- Prioritize data initiatives aligned with business value.
- Define and track delivery metrics for transparency and progression.
Vendor & Partner Ecosystem Management
- Manage relationships with external delivery partners and data platform vendors (e.g., Databricks).
- Align vendor capabilities with Wella’s delivery/expectations.
- Collaborate with Procurement and IT leadership on contract management, performance reviews, and cost optimization.
- Ensure compliance with InfoSec, data privacy, and enterprise technology standards.
Leadership & Organizational Development
- Lead multiple vendor squads, ensuring alignment, coordination, and delivery excellence.
- Establish clear governance, operating models, and ways of working for external teams.
- Serve as internal accountability point for all data delivery outcomes.
- Foster a culture of accountability, quality, and continuous improvement.
- Develop internal capabilities for managing and governed vendor-led delivery.
Essential Skills, Experience & Qualifications
Technical & Leadership Expertise
- Very strong technical and management skills in modern data architecture, engineering, and operations.
- Proven expertise in architecting and developing AI-enabled accelerators (e.g., ingestion, data quality, data mapping, ETL/ELTs).
- Deep knowledge of Databricks including environment setup, architecture, tooling, engineering, optimization, and operational delivery.
- Strong data engineering proficiency in implementing ingestion pipelines, transformations, and scalable products.
- Hands-on experience with MLflow and operationalizing machine learning workflows.
- Proven ability to manage third-party vendors, enforce accountability, and manage external squads.
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Verification & Certification
- Bachelor’s or master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
- Advanced certifications in data platforms, cloud technologies, or AI/ML are advantageous.
Experience Requirements
- 10–15 years in data engineering/analytics/IT delivery roles.
- 10–15 years (or equivalent) with Databricks (env. setup, ingestion frameworks, optimization).
- Strong practical experience with MLflow and the ML lifecycle.
- Demonstrated expertise managing vendor-led delivery.
- Proven leadership in potentially large, hybrid teams.
- Experience with data governance, data classification, and data quality.
- Proven experience creating AI-ready datasets at scale.
- Strong proficiency in Python, SQL, and Spark-based processing.
- Familiarity with SAP ecosystems: BDC, Datasphere, SAP data integration.
- Knowledge of enterprise ERP models and business process domains.
What We Offer
- Leave: 25 days (annual holiday) + extra day for your birthday (+ bank holidays).
- Personal leave: 3 days for significant life events.
- Volunteering: 2 paid days off for charity/volunteering work.
- Retirement: Optional Wella Pension Scheme (8% employee contribution + 3% company contribution).
- Insurance:
- Family private medical
- Income protection
- Age reportedly, Life insurance (8x salary, capped at £2 million).
- Staff Discounts:
- 80% off all hair products
- 40% discount at OPI
- Exclusive discounts on ghd products
- Support programs:
- Employee Assistance Program (EAP)
- Enhanced maternity/paternity/adoption leave
- Gym, wellness, and eye tests
- Work Culture & Perks:
- WOW Program (Bonus post KKR exit, eligible post probation)
- Nursery/workplace benefits
- 4 weeks remote work abroad
- Early Friday finish during summer.
EEO Equality, Diversity & Inclusion
Wella Company is committed to:
- Freedom from discrimination per the UK’s Equality Act 2010.
- Equality and Diversity as central to its business strategy.
- Providing equal employment opportunities regardless of:
- Race
- Age
- Gender
- Sexual orientation
- Disability
- Religion
- Veteran Status
For reasonable accommodations, contact: Wella Company Consumer Affairs
SE/EE OFE All protected.
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Skills
Databricks
Data Engineering
MLflow
Python
SQL
Spark
SAP Datasphere
Vendor Management
Data Governance
MLOps
CI/CD
Data Architecture
Stakeholder Management
ETL/ELT
Data Quality Frameworks
Cloud Technologies