Senior Analytics Engineer
Role details
Job location
Tech stack
Job description
The Data team is responsible for leveraging data to drive strategic business decisions and enhance our product offerings. As a core member, you will be responsible for end-to-end data projects-from defining metrics and building robust data pipelines to deploying analytical models. Your insights will be essential for monitoring company performance, understanding user behavior across various protocols, and contributing directly to Ledger's growth and security strategies. If you are a data professional passionate about the intersection of data science and the cutting-edge Web3 ecosystem, and you want to work in an environment that champions innovation, security, and decentralization, this role is for you., * Data Architecture & Modeling: Design, build, and maintain robust, scalable data pipelines (ELT) using dbt and Airflow, ensuring our Snowflake warehouse is optimized for both performance and clarity.
- Complex Data Mapping: Bridge the gap between raw, unstructured technical data (including on-chain events) and clean, actionable business entities.
- Stakeholder Partnership: Act as a technical partner to Product, Engineering, and Finance teams, translating high-level business questions into technical requirements and analytical frameworks.
- Analytics Engineering Excellence: Implement version control, CI/CD for data, and automated testing to ensure the highest levels of data quality and reliability.
- Strategic Insights: Perform deep-dive analyses to track revenue, identify user segments, and optimize product features in an industry that moves at lightning speed., At Ledger, we are dedicated to continually investing in our employees which is why we offer more than just salaries; we provide comprehensive compensation packages that include a wide range of benefits. Here are some of the benefits you can look forward to:
- Flexible work options - Our hybrid policy allows employees to work from home up to 3 times per week
- Health & Wellness support - Health and Life Insurance.
- Financial growth opportunities - Employees can become shareholders in Ledger as well as other financial benefits depending on your country of work.
- Commuter allowance - Ledger offers a commuter allowance to contribute to your preferred means of transportation.
- Learning & Development - A comprehensive suite of training solutions providing a personalised learning experience for every employee.
For regionally specific benefits, your Talent Acquisition contact will be able to provide you with more information.
We're committed to building an inclusive hiring process. If you need any adjustments or accommodations, just let us know, we'll do our best to support you.
Requirements
Do you have experience in Python?, * Experience: 4+ years (Senior level) of professional experience in Analytics Engineering, Data Engineering, or a Data Science role.
- SQL Mastery: Exceptional proficiency in SQL. You should be comfortable with complex window functions, performance tuning, and modeling in Snowflake.
- Modern Data Stack: Deep experience with dbt (data modeling, macros, testing) and workflow orchestrators like Airflow.
- Python Proficiency: Strong programming skills in Python for data manipulation, automation, and building data-intensive applications.
- Engineering Mindset: You treat data code like software-version control (Git), documentation, and modularity are second nature to you.
Bonus points
- Curiosity for Web3: You don't need to be a blockchain expert yet, but you should be excited to learn how Ethereum, Bitcoin, and DeFi protocols function.
- Advanced Analytics: Experience with time-series analysis, anomaly detection, or predictive modeling.
- Blockchain Exposure: Any previous experience with on-chain data (e.g., Dune Analytics, Flipside, or indexing protocols) is a major advantage.