Senior Manager, Marketing Intelligence

Snowflake
London
1 month ago
Applications closed

Related Jobs

View all jobs

Global Marketing Activation & Orchestration Senior Manager

Senior AI Product Manager Product - AI · London ·

Senior Specialist Technical Account Manager - AI/ML, ES - EMEA-STAM

Strategic Agency Sales Manager

Product Manager (Mid)

Front Office Data Analyst Engineer

Build the future of the AI Data Cloud. Join the Snowflake team.

Snowflake is growing fast and we’re scaling our team to help enable and accelerate our growth. We’re passionate about our people, our customers, our values and our culture! We’re also looking for people with a growth mindset and the pragmatic insight to solve for today while building for the future. And as a Snowflake employee, you will be accountable for supporting and enabling diversity and belonging.

Snowflake started with a clear vision: make modern data warehousing effective, affordable, and accessible to all data users. Because traditional on-premises and cloud solutions struggle with this, Snowflake developed an innovative product with a new built-for-the-cloud architecture that combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a fraction of the cost of traditional solutions.

OurData Analytics Officeis actively seeking a Senior Manager in Marketing Intelligence to contribute to building our framework to monitor health of business through metrics analysis. Examples of deliverables include QBR, performance and ROI analysis and deep dive.

Reporting to the Senior Director of GTM Analytics, you'll lead a global team transforming marketing data into actionable intelligence, driving real-time ROI optimization across international markets. This role combines technical expertise with strategic leadership to deliver impactful insights that directly influence our go-to-market strategy and business growth. Working with stakeholders across multiple regions, you'll champion data-driven decision making and advance our mission of revolutionizing B2B marketing analytics practices. 

In this role you will: 

Lead and mentor a distributed team of Business Intelligence Analysts, fostering innovation and professional growth

Partner with Marketing executives to align analytics initiatives with global business objectives and provide strategic recommendations

Design and deploy sophisticated analytics models and dashboards that guide marketing strategy and investment decisions across regions

Drive quarterly business reviews with data-driven insights and performance analyses for global marketing campaigns

Spearhead data infrastructure improvements and champion best practices in data governance

Present complex analytical findings to executive stakeholders with clarity and impact

Establish thought leadership in the business intelligence space, representing the company at industry events

Create and maintain project roadmaps that align with company OKRs and cross-regional marketing priorities

Required Skills: 

Bachelor's degree in a quantitative discipline (Information Systems, Mathematics, Statistics, Engineering, Computer Science, or related field)

8+ years of experience in data analytics, with at least 3+ years in people management

Advanced expertise in SQL and experience with MPP databases (Snowflake, Redshift, BigQuery)

Strong proficiency in Python for data transformation and analysis

Experience with BI tools (Streamlit, Tableau, Sigma, or similar)

Technical background in data pipeline development using tools like Airflow and dbt

Proven experience with B2B marketing technology stack (Salesforce, Marketo/Eloqua/HubSpot)

Track record of supporting executive reporting and strategic decision-making

Excellent communication skills with ability to work across different cultures and time zones

We’re looking for people who share our passion for ground-breaking technology and want to create a lasting future for you and Snowflake.

Are you up for the challenge?

Snowflake is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, color, gender identity or expression, marital status, national origin, disability, protected veteran status, race, religion, pregnancy, sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.

Career Paths in Machine Learning: From Entry-Level Roles to Leadership and Beyond

Machine learning has rapidly transformed from an academic pursuit to a cornerstone of modern technology, fueling innovations in healthcare, finance, retail, cybersecurity, and virtually every industry imaginable. From predictive analytics and computer vision to deep learning models that power personalisation algorithms, machine learning (ML) is reshaping business strategies and creating new economic opportunities. As demand for ML expertise continues to outstrip supply, the UK has become a vibrant hub for machine learning research, entrepreneurship, and corporate adoption. Whether you’re just starting out or have experience in data science, software development, or adjacent fields, there has never been a better time to pursue a career in machine learning. In this article, we will explore: The growing importance of machine learning in the UK Entry-level roles that can kick-start your ML career The skills and qualifications you’ll need to succeed Mid-level and advanced positions, including leadership tracks Tips for job seekers on www.machinelearningjobs.co.uk By the end, you’ll have a clear view of how to build, grow, and lead in one of the most exciting fields in modern technology.