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For Companies At a Glance
- Tasks: Analyse revenue data and provide insights to drive growth and inform strategies.
- Company: Join DeepL, a global leader in Language AI, breaking down communication barriers.
- Benefits: Enjoy hybrid work, flexible hours, 30 days annual leave, and virtual shares.
- Why this job: Be part of a dynamic team making a real impact in the fast-paced AI industry.
- Qualifications: 5+ years in revenue analytics; strong SQL and Python skills required.
- Other info: Collaborative culture with regular team events and opportunities for personal growth.
The predicted salary is between 36000 - 60000 £ per year.
DeepL is a global communications platform powered by Language AI. Since 2017, we’ve been on a mission to break down language barriers. Our human-sounding translations and intelligent writing suggestions are designed with enterprise security in mind. Today, they enable over 100,000 businesses to transform communications, reach new markets, and improve productivity.
This role is part of the Revenue Intelligence team within the GTM Operations organisation. The Revenue Intelligence team is a group of data scientists, analysts, and analytics engineers that supports the GTM Operations organisation by informing decision-making and driving revenue growth with data-driven insights. As the Revenue Analytics Engineer - Finance, you will partner closely with the Financial Planning & Analytics (FP&A) team and manage the Annual Recurring Revenue (ARR) pipeline. You will identify trends and insights to help understand business performance and inform the organisational growth strategy.
Your Responsibilities
- Financial Metric/Pipeline Ownership: Define, maintain, and optimise key financial pipelines (e.g. ARR), translating business requirements into SQL, and ensuring accurate tracking and reporting of key metrics.
- Data Analysis & Insights: Analyse revenue data to identify trends, anomalies, and growth opportunities; provide actionable insights to the FP&A team and other stakeholders.
- Reporting & Visualisation: Develop and maintain dashboards and reports that effectively communicate financial performance and forecasts to senior management and cross-functional teams.
- Collaboration: Work closely with the VP of FP&A and other teams to align revenue analytics with financial planning and operational strategies; partner with sales, marketing, and product teams to gather and analyze relevant data.
- Process Improvement: Identify and implement process improvements to enhance the efficiency and accuracy of revenue reporting and analytics.
- Technical Expertise: Utilise SQL, BI tools, and Python (where necessary) to extract, manipulate, and analyse large datasets.
- Stakeholder Engagement: Present findings and recommendations to stakeholders at various levels of the organisation, fostering a data-driven culture.
Qualities we look for
- Education: Bachelor’s degree in Finance, Business, Data Science, or a related field; Master’s degree preferred.
- Experience: Minimum of 5 years of experience in revenue analytics, financial analysis, or a related field, with a strong focus on subscription-based business models.
- Data Modeling: Expertise in designing and implementing data models for analytics, using data orchestration and transformation tools like dbt and Airflow.
- SQL: Advanced proficiency in writing complex queries and optimizing performance.
- Python: Experience in data manipulation and scripting.
- Data Warehouse: Hands-on experience with data warehouses; experience with cloud data warehouses (Snowflake, Databricks, or BigQuery) preferred.
- Familiarity with GTM metrics and financial modeling.
- Product mindset: Able to work directly with business stakeholders to translate analytics needs into user-friendly, highly-performant data products.
- Analytical Mindset: Strong analytical skills with the ability to use BI tools (e.g. Tableau/Metabase) to interpret and visualise complex data and provide actionable insights.
- Communication Skills: Excellent verbal and written communication skills, with the ability to present complex information clearly and concisely to diverse audiences, including senior stakeholders.
- Problem-Solving: Proven ability to think critically and solve complex problems independently.
Nice-to-Haves
- Experience in a SaaS or technology company, particularly in revenue operations or financial planning.
- Knowledge of Salesforce and its integration with financial data.
- Experience with machine learning or advanced analytics techniques.
- Strong project management skills and experience working in cross-functional teams.
What We Offer
- Diverse and internationally distributed team: joining our team means becoming part of a large, global community with people of more than 90 nationalities.
- Open communication, regular feedback: we value the importance of clear, honest communication.
- Hybrid work, flexible hours: we offer a hybrid work schedule, with team members coming into the office twice a week.
- Virtual Shares: every employee receives Virtual Shares, linking your contribution directly to DeepL’s growth.
- Regular in-person team events: we bond over vibrant events that bring us all together.
- Monthly full-day hacking sessions: every month, we have Hack Fridays, where you can dive into a project you’re passionate about.
- 30 days of annual leave: we value your peace of mind.
- Competitive benefits: we’ve crafted our benefits package to reflect the diversity of our team.
Equal Opportunity
You are welcome at DeepL for who you are—we appreciate authenticity here. Our product is for everyone, and so is our workplace.
Revenue Analytics Engineer employer: DeepL
Contact Detail:
DeepL Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Revenue Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at DeepL. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Show off your skills! Prepare a mini-project or case study related to revenue analytics. This will not only demonstrate your expertise but also give you something tangible to discuss during interviews.
✨Tip Number 3
Be ready to talk numbers! Brush up on your financial metrics and be prepared to discuss how you've used data to drive decisions in past roles. Confidence in your analytical skills is key!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in being part of the DeepL team.
We think you need these skills to ace Revenue Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Revenue Analytics Engineer role. Highlight relevant experience in revenue analytics, financial analysis, and any specific tools like SQL or Python that you’ve used. We want to see how your skills align with what we’re looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you’re passionate about the role and how your background makes you a great fit. Don’t forget to mention your interest in working with a dynamic team in the AI space – we love that enthusiasm!
Showcase Your Analytical Skills: In your application, be sure to showcase your analytical mindset. Share examples of how you've used data to drive insights or improve processes in previous roles. We’re all about data-driven decision-making, so let us see your skills in action!
Apply Through Our Website: We encourage you to apply through our website for the best experience. It’s super easy, and you’ll get to see all the details about the role and our company culture. Plus, it helps us keep track of your application better!
How to prepare for a job interview at DeepL
✨Know Your Numbers
As a Revenue Analytics Engineer, you'll be dealing with financial metrics like ARR. Brush up on these key figures and be ready to discuss how you've used data to drive revenue growth in your previous roles. This shows you understand the business side of analytics.
✨Showcase Your Technical Skills
Be prepared to demonstrate your SQL prowess and familiarity with BI tools. You might be asked to solve a problem on the spot, so practice writing complex queries and visualising data. Highlight any experience with Python or cloud data warehouses, as these are crucial for the role.
✨Communicate Clearly
You'll need to present findings to senior stakeholders, so practice explaining complex data insights in simple terms. Use examples from your past experiences where you successfully communicated analytical results to non-technical audiences. This will show your ability to bridge the gap between data and decision-making.
✨Emphasise Collaboration
This role involves working closely with various teams, including FP&A and sales. Be ready to discuss how you've collaborated in cross-functional settings before. Share specific examples of how your teamwork led to improved processes or outcomes, demonstrating your ability to work well in a dynamic environment.
