Stats Jobs at Ramp

🙌🏼 What you will be doing

We are a well-established Data Team within the organization, having evolved from our initial focus on data integration, sustainable descriptive analytics, and A/B testing to now encompass predictive and prescriptive analytics fully.

In your capacity as an Analytics Engineer, you will forge strong partnerships with Product, Design, and Engineering teams, guiding data-driven decisions that shape our future product directions. Your technical skills will be utilised across a spectrum of product domains.

🙌🏼 Your future contributions

• Drive the design and evolution of our dbt models to support decision-making processes and inspire data-driven innovation across product and business strategies.
• Implement comprehensive data quality tests within our existing framework to ensure model integrity, fostering a data-trust culture.
• Architect and document scalable model frameworks that underpin our analytics infrastructure.
• Develop and uphold code standards for >
• Enhance our BigQuery utilization through optimized data modeling and query designs, contributing to the scalability and efficiency of our data operations.

🧩What you will be working on

• Developing and managing a modular data architecture, primarily leveraging dbt and BigQuery, to support robust data visualizations and insights.
• Contributing to the enhancement of data quality and security standards.
• Reviewing the contribution of other team members to our common dbt repo.
• Support the Analysts’ Community in:
  • Automating the reporting of critical business metrics, aligning with our strategic goals.
  • Championing data best practices in collaboration with the broader Data team.
  • Analyzing a variety of data, including transactional (with a focus on cryptocurrency transactions), KYC, AML, alongside data from event-based analytics tools, customer support feedback, and more.
  • Addressing complex business challenges through innovative data analytics solutions in partnership with key internal stakeholders.
  • Effectively communicating insights and findings to a diverse audience, bridging the gap between technical and non-technical realms.

⚙️Our tech stack:

• Google Cloud Platform, with a focus on BigQuery
• dbt
• Tableau (at the moment)
• git
• Secoda
• Elementary
• Supplementary tools: Figma, Figjam, VS Code

🤟What you will bring:

• Over 3 years of experience in a data-centric role, ideally with a significant portion dedicated to analytics engineering.
• Demonstrated expertise in data modeling, ETL processes, and the construction of scalable data infrastructures.
• Leadership skills that include task delegation and workload management, with a proven track record of mentoring team members on code quality and sustainability.
• Solid communication abilities, capable of demystifying complex data insights for varied audiences.
• A proactive problem-solver with a continuous improvement mindset, eager to drive changes that enhance team productivity.
• Commitment to personal and professional growth, keeping abreast of the latest industry trends and technologies.
• A collaborative team player, excited by the prospect of innovating at the intersection of FinTech and blockchain technology.

🪄What’s in it for you?

💸 Competitive salary

• Equity package: share in our success
• Zero-fee crypto purchases via on-ramp!

🩺 Health & wellbeing

• 26+ days paid time-off
• Health & Sports benefits for you and your loved ones
• Dedicated time off for yearly health check-ups

🧠 Development & Growth

• Self-development and conference budget
• Language lessons
• Internal workshops and activities supporting growth and mental health

🏢 Great working environment and socials

• Modern and comfy offices in Warsaw and Wroclaw, which has everything you'll need to excel and collaborate with your team
• Remote working with visits in our offices
• The best laptops and kit to work on
• Internal Tech meetups on-site & online
• Team socials funded by us

🤝Our interview process

1. Discovery phone interview with a recruiter (30 minutes).
2. Technical and Life>
3. Interview with a domain specialist and Head of Data (30 minutes).