At a Glance
- Tasks: Lead the delivery of innovative data solutions and drive Wella's data transformation.
- Company: Join Wella, a leader in beauty tech with a focus on data-driven innovation.
- Benefits: Enjoy competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Be part of a diverse team committed to equality and continuous improvement.
- Why this job: Make a real impact by shaping AI-ready data platforms that power analytics and machine learning.
- Qualifications: 10-15 years in data engineering with expertise in Databricks and ML lifecycle management.
The predicted salary is between 80000 - 100000 £ per year.
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 that enterprise data is accessible, governed, and optimized for advanced analytics and AI use cases. Working in close partnership with the Data architecture and Enterprise Architecture teams, this position translates architectural designs into high-quality, production-ready data products. The role is accountable for executing against defined architectures, ensuring adherence to standards while delivering reliable and scalable solutions.
As a key partner to business and technology stakeholders, this role is responsible for delivering robust data pipelines, platforms, and products that power analytics, reporting, and machine learning initiatives. It has deep expertise in Databricks and modern data engineering practices, including environment setup, ingestion frameworks, ML lifecycle management (MLflow), and scalable coding practices. This role leads delivery through internal and external vendor squads and is accountable for ensuring high performance, quality, and timeliness of delivery.
Key Responsibilities:
- Data Platform Architecture, Delivery & Engineering Execution & Operations: Own the end-to-end delivery of data solutions on platforms (Databricks & SAP), ensuring alignment with enterprise architecture principles. Oversee setup, configuration, and optimization of data environments to ensure 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. Establish & Lead Data Solution Architecture practice to ensure design integrity and proper 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 delivery expectations, SLAs, KPIs, and acceptance criteria for all vendor teams. Hold vendors accountable for performance, quality, and adherence to engineering and governance standards. Establish robust governance frameworks, including sprint reviews, delivery checkpoints, and performance tracking. Proactively manage delivery risks, issues, and dependencies, ensuring rapid resolution and minimal business impact. Drive continuous improvement in vendor performance, productivity, and delivery outcomes.
- Solution Delivery, Operations & Lifecycle Management: Ensure end-to-end accountability for the lifecycle of data products—from ingestion to consumption. Establish & manage disciplined release management, testing, and deployment practices. Ensure platform reliability, stability, and scalability across all data workloads. Optimize data processing performance and cost efficiency. Act as the escalation point for delivery and operational issues related to data pipelines and platforms.
- Data Governance, Quality & AI Readiness: Establish and implement enterprise data governance standards and policies. Implement and enforce data classification standards aligned with enterprise data governance policies. Drive data quality frameworks, including monitoring, validation, and issue remediation. Ensure data is structured, cataloged, and accessible for analytics and AI use cases. Champion the creation of 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 and analytics teams to translate requirements into scalable data solutions. Enable advanced analytics, reporting, and AI initiatives through high-quality, reliable data delivery. Drive prioritization of data initiatives aligned with business value and outcomes. Define and track delivery metrics, ensuring transparency into progress and value realization.
- Vendor & Partner Ecosystem Management: Manage relationships with external delivery partners and data platform vendors (e.g., Databricks). Ensure alignment between vendor capabilities and Wella’s delivery and quality 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 across all vendor-delivered solutions.
- Leadership & Organizational Development: Provide leadership across multiple vendor squads, ensuring alignment, coordination, and delivery excellence. Establish clear delivery governance, operating models, and ways of working for external teams. Act as the internal point of accountability for all data delivery outcomes. Foster a culture of accountability, quality, and continuous improvement across internal and external teams. Develop internal capabilities to effectively manage and govern vendor-led delivery models.
Essential Skills, Experience & Qualifications:
- Very strong technical & management expertise in modern data architecture, engineering and operational efficiencies.
- Proven experience architecting and developing AI enabled accelerators for various data management use cases (ingestion, DQ, data mapping, ETL/ELTs etc.).
- Databricks Platform Expertise – deep experience with Databricks, including environment setup, architecture, tooling, engineering, optimization, and operational delivery.
- Data Engineering Delivery – strong expertise in implementing ingestion pipelines, transformations, and scalable data products.
- ML Lifecycle Enablement – hands-on experience with MLflow and operationalizing machine learning workflows.
- Vendor & Delivery Management – proven ability to manage third-party vendors, enforce accountability, and deliver through external squads.
- Governance & Accountability – strong experience establishing delivery governance, KPIs, and performance management frameworks.
- Data Governance & Quality – experience implementing data classification, quality controls, and governance processes.
- AI Data Enablement – proven ability to prepare and deliver AI-ready datasets for advanced analytics.
- Technical Depth & Coding – strong programming skills (Python, SQL, Spark) with focus on quality and maintainability.
- Stakeholder Management – ability to translate business needs into actionable data delivery outcomes.
Qualifications & Experience:
- Education: 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 a plus.
- Experience: 10-15 years of experience in data engineering, data platforms, or analytics delivery roles. Proven hands‑on experience with Databricks, including environment setup, ingestion frameworks, and optimization. Strong experience implementing MLflow and supporting machine learning lifecycle management. Demonstrated experience managing delivery through third‑party vendors or system integrators. Proven leadership in overseeing multiple delivery squads (vendor or hybrid models). Strong experience in data governance, data classification, and data quality implementation. Proven ability to deliver AI‑ready data solutions at scale. Strong coding experience in Python, SQL, and Spark‑based processing. Experience with SAP data ecosystems, including SAP BDC, Datasphere, and SAP data integration. Familiarity with enterprise ERP data models and business process data domains.
EEO Opportunities:
The Wella Company wants to meet the aims and commitments set out in its equality policy. This includes not discriminating under the Equality Act 2010 and building an accurate picture of the make‑up of the workforce in encouraging equality and diversity. We offer equal employment opportunity to qualified individuals without regard to race, religion or belief, color, national origin, age, gender, disability, sexual orientation, gender identity, gender expression, marital or civil partnership, pregnancy and maternity, veteran status, or any other characteristic protected by law. Wella Company with federal and state disability laws and makes reasonable accommodations for applicants and employees with disabilities. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact us at: https://www.wellacompany.com/consumer-affairs. We strongly believe that cultivating a diverse workplace gives a company strength. The combination of unique skills, abilities, experiences and backgrounds creates an environment that produces extraordinary results.
Director, Data Delivery employer: Wella Company
Wella Company is an exceptional employer located in the vibrant city of London, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from extensive growth opportunities, including leadership development and access to cutting-edge technology, while being part of a diverse team committed to driving data-driven transformation. With a focus on quality, accountability, and continuous improvement, Wella empowers its workforce to deliver impactful solutions in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Director, Data Delivery
✨Tip Number 1
Network like a pro! Reach out to your connections in the data and analytics field. Attend industry events, webinars, or even local meetups. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving Databricks or MLflow. This gives potential employers a tangible sense of what you can do and how you approach data challenges.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering scenarios. Be ready to discuss your experience with data pipelines, governance, and AI readiness. Practising answers to technical questions will help you feel more confident when it’s time to shine.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Director, Data Delivery
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with data platforms, especially Databricks. We want to see how your skills align with the role of Director, Data Delivery, so don’t hold back on showcasing your relevant achievements!
Showcase Your Leadership Skills:As a strategic leader, it’s crucial to demonstrate your ability to manage teams and vendors effectively. Share examples of how you've led data delivery projects or improved processes in previous roles. We love seeing candidates who can inspire and drive results!
Highlight Technical Expertise:Don’t forget to mention your technical skills, especially in data engineering and AI readiness. We’re looking for someone with strong programming abilities in Python, SQL, and Spark, so make sure these stand out in your application.
Apply Through Our Website:We encourage you to submit your application through our website for the best chance of being noticed. It’s the easiest way for us to keep track of your application and ensure it gets to the right people!
How to prepare for a job interview at Wella Company
✨Know Your Data Inside Out
Make sure you have a solid understanding of data platforms, especially Databricks. Brush up on your knowledge of data ingestion processes, transformation pipelines, and how to optimise data environments for performance and scalability. Being able to discuss these topics confidently will show that you're the right fit for the role.
✨Showcase Your Leadership Skills
As a Director, you'll need to demonstrate your ability to lead teams and manage vendor relationships. Prepare examples of how you've successfully overseen delivery squads in the past, ensuring high-quality outcomes. Highlight your experience in establishing governance frameworks and driving accountability among team members.
✨Prepare for Technical Questions
Expect to face technical questions related to data engineering and AI readiness. Be ready to discuss your hands-on experience with MLflow and machine learning workflows. Practise explaining complex concepts in simple terms, as this will help you connect with both technical and non-technical stakeholders during the interview.
✨Align with Business Goals
Understand how data delivery impacts business outcomes. Be prepared to discuss how you've translated business needs into actionable data solutions in previous roles. Showing that you can prioritise data initiatives based on business value will set you apart as a candidate who truly understands the strategic importance of the position.