At a Glance
- Tasks: Lead transformative data and AI projects, ensuring quality delivery and client satisfaction.
- Company: Join Slalom, a purpose-driven consulting firm with a focus on innovation and impact.
- Benefits: Enjoy competitive pay, flexible work-life balance, and a supportive, inclusive culture.
- Other info: Opportunity for career growth and mentorship in a dynamic, collaborative environment.
- Why this job: Shape the future of data while working with top tech partners and diverse teams.
- Qualifications: 10+ years in data programmes, strong stakeholder management, and commercial acumen required.
The predicted salary is between 80000 - 100000 £ per year.
- We have a question for you
- and it’s something we’re really passionate about.
Can you imagine a world in which you can truly love your life and your work?
Creating that world is what we get out of bed for — it’s our north star.
But what do we mean by loving your life and work? Let’s take a look.
Deep connections, better outcomes
We have deep relationships with over 400 leading technology partners and deliver innovative, outcome-based solutions alongside our clients.
Flexibility
We support our people in balancing work, family, and personal commitments while working on impactful projects.
People-first
We empower people to be their authentic selves, fostering inclusion, diversity, and a strong sense of belonging.
Rewards
We offer competitive, fair, and rewarding compensation and benefits.
Take a look at the role below and apply if it sparks your interest.
Slalom's Data Capability
At Slalom, we believe trusted relationships and modern data platforms unlock extraordinary outcomes.
Our Data Capability spans strategy, architecture, engineering, analytics, and AI.
We are technology-agnostic, working across Snowflake, AWS, Azure, Databricks, and GCP.
We partner closely with our technology alliances to co-create solutions, accelerators, and go-to-market offerings.
We're looking for curious, commercially minded individuals excited about shaping the future of data.
Data Delivery Owner
As a Data Delivery Owner, you will lead large-scale, strategic data and AI transformation programmes, bridging business strategy and technical execution to deliver measurable outcomes.
You will act as a trusted advisor to executives and delivery teams, combining programme leadership, commercial acumen, and deep data expertise.
What will you do?
- Lead large-scale data and AI transformation programmes, managing scope, timelines, budgets, risks, and resources.
- Oversee a portfolio of concurrent engagements, accountable for delivery quality, margin, and client satisfaction.
- Drive organisational change through data delivery.
- Delivery & Solution Ownership
- Own delivery across complex, multi-capability engagements.
- Partner with Solution Architects and workstream leads to define scalable solutions.
- Manage vendors and technology partners.
- Stakeholder Engagement & Client Advisory
- Act as liaison between business and technical teams.
- Advise C-suite stakeholders on data strategy and transformation roadmaps.
- Build lasting client relationships.
- Support strategic data pursuits and large engagements.
- Ensure seamless transition from sales to delivery.
- Develop proposals and statements of work.
- Coach teams on agile delivery practices.
- Enable teams to deliver with pace and quality.
- Practice Development & Thought Leadership
- Build and scale data delivery capability and frameworks.
- Mentor and develop Data Delivery Owners.
- Contribute to thought leadership externally.
- What you'll bring
- 10+ years delivering large-scale data programmes in consulting.
- Ability to influence C-suite stakeholders.
- Strong knowledge of modern data platforms and architecture.
- Strong commercial acumen and pursuit experience.
- Excellent communication and stakeholder management.
- Experience managing vendors and partners.
- Success Metrics
- Delivery quality, margin, and client satisfaction
- Contribution to pursuit wins and proposals
- Utilisation aligned to expectations
- Adoption of delivery methodologies and accelerators
- Growth of delivery team capability
About us – Slalom
Slalom is a purpose-led, global business and technology consulting company delivering practical, end-to-end solutions that drive meaningful impact.
Our 13,000+ team works across global markets, partnering with leading technology providers to help organisations move faster and build better futures.
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StudySmarter Expert Advice🤫
We think this is how you could land Technical Project Manager -Data Delivery Owner in Manchester
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Slalom!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Technical Project Manager -Data Delivery Owner at Slalom.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Slalom.
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We think you need these skills to ace Technical Project Manager -Data Delivery Owner in Manchester
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Slalom, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Slalom. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Slalom
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Slalom!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
