Senior Analytics Engineer
hace 1 semana
At Tala, we're applying advanced technology and human creativity to solve what legacy institutions can't or won't. We are a global financial infrastructure company on a mission to unleash the economic power of the global majority, recognizing that today's financial infrastructure doesn't work for most of the world's population.
Our pioneering work and proven impact have earned us consistent recognition, including being named to:
CNBC's Disruptor 50 for five years. CNBC's World's Top Fintech Companies for two consecutive years. Forbes' Fintech 50 list for nine consecutive years.
Visionary investors, persuaded by the economic power of the global majority, have committed half a billion dollars in equity and debt to Tala's success.
Given the global nature of our team, we operate on a remote-first approach with office hubs in Santa Monica, CA (HQ); Nairobi, Kenya; Mexico City, Mexico; Manila, the Philippines; and Bangalore, India.
Most Talazens join us because they connect with our mission. If you are energized by the impact you can make at Tala, we'd love to hear from you
The Role We're looking for a Senior Analytics Engineer to elevate how data powers decisions across our company. In this role, you'll own the design, development, and optimization of our presentation layer—transforming raw data into trusted, accessible insights for business and product teams. You'll partner with data engineers, analysts, and business stakeholders to evolve our data ecosystem, ensure data reliability, and drive scalable best practices that make analytics faster, clearer, and more impactful.
This is a hands-on, high-visibility role for someone who loves solving complex data challenges, mentoring others, and building the foundation that empowers a data-driven culture. What You'll Do
- Own the presentation layer: Design, build, and maintain dbt models and Snowflake data marts that power dashboards, reports, and key business metrics.
- Evolve our data infrastructure: Lead initiatives around new data architecture, warehouse optimization, and data governance.
- Bridge data and business: Partner with analysts, product managers, and operations to translate questions into scalable data models and clear insights.
- Drive best practices: Champion code quality, documentation, and version control (GitHub), while mentoring peers on modern analytics engineering patterns.
- Ensure reliability: Monitor data pipelines, manage warehouse performance, and implement alerting or cost-optimization strategies (e.g., warehouse sizing, query tuning).
- Enable self-service: Build semantic layers and train teams to use data confidently through tools like Looker, Omni, or Hex.
- 5+ years of experience as an Analytics Engineer, Data Engineer, or BI Engineer, working with modern data stacks
- Deep expertise in SQL, DBT, and Snowflake (both development and warehouse management)
- Strong proficiency in at least one programming language such as Python or Java
- Proven track record of designing scalable data models and ETL pipelines for analytical consumption
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