Senior Analytics Engineer
A complete suite of trusted products to build anything in web3
Projects
About Consensys
Consensys is the leading blockchain and web3 software company. Since 2014, Consensys has been at the forefront of innovation, pioneering technological developments within the web3 ecosystem. Through our product suite, we have become a trusted collaborator for users, creators, and developers. Whether building a dapp, an NFT collection, a portfolio, or a better future, the instinct to build is universal. Our mission is to inspire and empower the builder in everyone by making web3 universally easy to use and develop on. Let’s build the world we want to see.
Skills
About the Role
You will design, build, and maintain reliable data models and transformation pipelines that turn raw data into business-ready datasets. You will define and implement metrics and semantic layers, write efficient SQL and dbt transformations, ensure data quality and governance, and create dashboards and reports to enable data-driven decisions.
Requirements
- Over 6 years of experience as a Analytics Engineer
- Previous experience developing and tracking KPIs for public companies
- Expert-level SQL skills with experience writing complex queries and optimizing performance
- Hands-on experience with dbt for data transformation and modeling
- Strong understanding of data modeling concepts such as star schema snowflake schema and dimensional modeling
- Familiarity with BI and dashboarding tools such as Looker Superset Tableau Power BI
- Experience defining KPIs and metrics for business stakeholders
- Comfort with Python or other scripting languages for lightweight data transformations and automation
- Knowledge of data governance lineage and documentation tools such as DataHub Great Expectations
- Understanding of cloud data warehouses such as Snowflake BigQuery Redshift
- Experience with version control and CI/CD practices in analytics workflows such as GitHub Actions
Responsibilities
- Design build and maintain reliable data models that transform raw data into business-ready datasets
- Collaborate with analysts data scientists and business stakeholders to translate requirements into actionable metrics and KPIs
- Develop and maintain metrics definitions semantic layers and data documentation to ensure consistency
- Build optimize and test dbt models to deliver clean reliable and trusted data
- Ensure data quality accuracy and governance are embedded in models and pipelines
- Create dashboards reports and visualizations that empower business users to make data-driven decisions
- Write efficient SQL queries and maintain performant models
- Partner with data engineers to ensure smooth data ingestion and availability for analytics
- Continuously improve processes and workflows to increase efficiency reliability and scalability